77 AI Engineer jobs in the United Arab Emirates

The Role
Charterhouse is partnering with a fast-growing technology company pioneering the development of advanced server hardware tailored for artificial intelligence (AI) and machine learning (ML) workloads. Our Client is dedicated to accelerating AI innovation by delivering high-performance, scalable, and energy-efficient infrastructure solutions. As part of their expansion, they are looking to hire experienced AI Engineers (multiple openings) to join their team. The AI Engineer will be responsible for designing and implementing scalable systems based on large language models, leveraging Python and modern generative AI frameworks. In this role, the Engineer will contribute to the development of internal GenAI systems and demo applications that showcase the capabilities of the company’s proprietary hardware. Key responsibilities include optimizing prompts, embeddings, retrieval mechanisms, and model behaviour, as well as fine-tuning models to enhance domain-specific performance. The role requires building custom pipelines for document ingestion, chunking, embedding generation, and retrieval, in addition to maintaining workflows for model versioning, reproducibility, as well as experiment tracking. Furthermore, the AI Engineer will also collaborate with internal and external teams to define evaluation workflows for custom AI hardware and frameworks, and to profile AI workloads across diverse platforms.

Requirements
The successful candidate will demonstrate strong programming skills in Python and familiarity with data analysis libraries such as Pandas, NumPy, and SQL which are essential for the role. Hands-on experience deploying retrieval-augmented generation (RAG) solutions, working with vector databases (e.g., Milvus, Chroma), and utilizing evaluation frameworks such as Ragas or DeepEval is required. In addition, experience with large-scale deployment and monitoring tools (e.g., ClearML, Kubeflow) is also highly desirable, along with a solid understanding of software engineering best practices, including testing, debugging, documentation, and version control. Knowledge of CPU, GPU, or custom accelerator architectures such as NPUs, TPUs is preferred, but not mandatory.

About the company
The Charterhouse brand and business was launched in Dubai and the Middle East in April 2004 by a team of international recruiters and management consultants, after its inception in Sydney, Australia in September 2003. Charterhouse Middle East is now positioned as the leading regional recruiter within its area of disciplines and functional markets. Charterhouse offers professional and bespoke contingency and retained search services to all sectors of the market. Service quality is guaranteed, thanks to a particular focus on flexibility. Charterhouse was the first international search and selection business to establish Dubai as its base. The growth in the Middle East region has been mirrored by Charterhouse globally, with offices now in Qatar, Hong Kong, Singapore, Melbourne and Sydney.

The Role
ICB Labs is a dynamic blockchain ecosystem integrating NFTs, DeFi, and metaverse technologies to revolutionize how businesses and individuals interact with the digital world. ICB Labs is more than just a blockchain company it is a visionary hub where traditional industries seamlessly connect with Web3 technologies. We believe in the power of decentralization to foster innovation, transparency, and financial inclusivity. Our ecosystem is designed to empower users with accessible, efficient, and future-ready blockchain solutions. Key Responsibilities • Develop, train, and fine-tune machine learning models for various use cases (e.g., NLP, computer vision, recommendation systems, etc.) • Analyze large datasets to extract insights and prepare data for model training • Research and implement state-of-the-art algorithms in AI and deep learning • Build scalable and efficient model pipelines for production use • Monitor, test, and improve model performance and accuracy over time • Collaborate with data engineers and software developers to deploy models into production environments • Document processes, models, and decisions for technical transparency and reproducibility

Requirements
• Strong programming skills in Python and experience with ML libraries such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face • Hands-on experience in training models using supervised, unsupervised, or reinforcement learning • Solid understanding of machine learning fundamentals: feature engineering, model evaluation, overfitting, cross-validation • Experience with data preprocessing, cleaning, and transformation • Familiarity with version control tools (e.g., Git) and experiment tracking tools (e.g., MLflow, Weights & Biases) • Ability to write clean, scalable, and efficient code • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field Preferred Skills • Experience with cloud platforms (AWS, GCP, Azure) for AI/ML model deployment • Knowledge of MLOps tools and practices (Docker, Kubernetes, CI/CD pipelines) • Experience working with unstructured data (text, image, audio) • Understanding of large language models (LLMs), transformers, or generative AI systems • Contribution to open-source ML projects or published research in AI conferences (nice to have)

About the company
The premier marketplace for NFTs, where art, technology, and community converge to create a new era of digital ownership. Together, let's embark on a journey to discover, collect, and create the talents of the NFT universe.

Overview

Dubai, United Arab Emirates | Posted on 22/09/2025

Deriv is an AI-first company, transforming trading through cutting-edge technology. We are seeking a highly skilled Applied AI Engineer to join our dynamic team. You will play a key role in designing, developing, and deploying AI-driven solutions that power our internal tools, marketing automation, and security infrastructure.

Responsibilities

• Design, build, and operate agentic LLM applications with tool-use/function calling, planning, memory, and structured outputs with versioned prompts.
• Implement RAG pipelines (hybrid dense+sparse retrieval, reranking); manage vector indices and the embedding lifecycle.
• Integrate models with internal services and third-party APIs via tool adapters; enforce schema contracts and access controls.
• Lead feature work in recommendation/ranking, content generation/editing, and workflow orchestration backed by measurable eval metrics.

Security & Automation

• Build AI-driven security automations: classifiers/anomaly detectors, red-teaming harnesses, and (where appropriate) autonomous testing agents.
• Implement safety & privacy controls: prompt-injection/jailbreak defenses, PII redaction, policy filtering, and auditability.
• Stand up real-time tracing & alerts on token/latency/cost, retrieval degradation, drift, and hallucination risk.

Project & Task Management

• Own model/prompt/agent versioning and ship via CI/CD with canaries/A-B, rollback plans, and clear SLOs (quality, latency, cost).
• Evolve workflows: PR-based changes to prompts/configs, experiment tracking, concise design docs, and ADRs (decision records).

Quality Assurance & Code Review

• Enforce evaluation-first development: golden sets, synthetic probes, regression tests for prompts, grounding/faithfulness checks.
• Review for determinism, observability, and reproducibility; address tech debt with a bias to stability and measured impact.
• Partner with platform/data teams on data contracts, retrieval standards, and tenancy/access control.
• Mentor peers on agent patterns, RAG, prompt engineering, and safe rollout; lead design reviews and share practical research findings.
• Benchmark and integrate new model families/tools via standardized bake-offs; report quality–latency–cost trade-offs.
• Optimize serving with adapters/LoRA, distillation/quantization, routing/caching/speculative decoding; right-size infra for cost/perf.
• Track industry and research trends; convert into pragmatic, incremental stack upgrades.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
• Hands-on experience with cloud platforms (GCP, AWS, or Azure) and containerization (Docker, Kubernetes).
• Solid understanding of security best practices and experience with security automation is a plus.
• Excellent problem-solving, communication, and leadership skills.
• Experience with task management and code collaboration tools (GitHub, Jira, ClickUp, etc.).
• Ability to work independently and as part of a fast-paced, collaborative team.

Nice to Have

• Experience in AI/ML engineering, with a proven track record of delivering production-grade solutions.
• Experience with marketing automation, content generation, or design systems.
• Familiarity with Figma, Supabase, or similar platforms.
• Contributions to open source AI/security projects.
• Prior experience in a high-growth tech or fintech environment.

We pay competitive salaries based on your skills, qualifications, experience and market rates. Additionally, you’ll be eligible for an annual bonus based on individual and company performance.

When you join Deriv, you will be supported in growing your career in our company. You can expect to have a personalised Learning and Development programme as well as the costs covered for relevant professional development and education related to advancing your career at Deriv.

You’ll be based at our modern office in Dubai’s prestigious Business Bay, a key centre for Deriv’s Middle Eastern operations. Our Dubai office is home to over 200 talented professionals from diverse nationalities, creating a truly global workplace. You’ll thrive in an expat-friendly environment that celebrates diversity and encourages cross-cultural collaboration, with regular knowledge-sharing sessions and team events.

Dubai’s position as a global business hub, combined with its tax-free benefits, ultramodern lifestyle, and family-friendly environment with excellent schools and healthcare, creates the perfect setting for international professionals. Join us in Dubai to shape the future of online trading while experiencing life in one of the world’s most dynamic and cosmopolitan cities.

Our culture is unique, and we live by our values and leadership principles, so it's worth learning more about Deriv's culture.

Deriv is an equal opportunity employer committed to diversity and inclusion. We take pride in our Great Place to Work and IIP Platinum certifications, which reflect our commitment to creating an exceptional work environment. Join us and help build the future of online trading while working alongside top talent from over 96 nationalities.

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The Role
We are seeking a highly skilled Senior AI Engineer to lead the strategy, design, deployment, and optimization of advanced AI systems. This is a hands-on, technical leadership role responsible for driving machine learning (ML), computer vision, large language model (LLM), and MLOps initiatives. We are looking for a UAE National and the ideal candidate will bring deep expertise across the AI stack, from model architecture to deployment, and thrive in a collaborative, cross-functional environment. Key Responsibilities: - Design, develop, and train advanced computer vision models including CNNs, Vision Transformers, and diffusion models for tasks such as image/video understanding, segmentation, and generation. - Architect and implement on-premise large language models (LLMs) using platforms like Ollama, OpenWebUI, and PrivateGPT. This includes fine-tuning, quantization, and secure deployment. - Optimize LLM pipelines for tasks like translation, summarization, semantic search, and prompt-based reasoning, ensuring performance, latency, and cost efficiency. - Build and productionize retrieval-augmented generation (RAG) systems using frameworks such as LangChain and vector databases (e.g., Pinecone, FAISS, Milvus). - Establish and maintain robust MLOps practices, including containerization (Docker), orchestration (Kubernetes), CI/CD pipelines, monitoring, and automated retraining. - Develop and maintain REST and GraphQL APIs to serve ML models, manage inference workflows, and integrate with end-user applications. - Lead edge AI deployments on platforms such as NVIDIA Jetson, focusing on performance-optimized, low-latency inference at the edge. - Drive training and inference performance improvements using distributed training, mixed-precision computing, model parallelism, and tools like TensorRT, ONNX Runtime, and DeepSpeed. - Collaborate with stakeholders—product managers, engineers, QA, and operations teams—to translate requirements into AI-driven solutions. - Mentor junior engineers and promote best practices in experiment tracking, reproducibility, and knowledge sharing. - Create technical documentation, proof-of-concept prototypes, performance benchmarks, and cost analyses to support decision-making.

Requirements
Required Technical Skills and Experience: - UAE National - Bachelor's or Master’s degree in Computer Science, Engineering, AI/ML, or related field (PhD preferred). - Minimum 5 years of experience in building and deploying computer vision models using TensorFlow and PyTorch. - Experience with on-prem LLM hosting and customization (Ollama, PrivateGPT, OpenWebUI). - Strong understanding of LLM applications including summarization, translation, prompt engineering, and semantic search. - Experience in RAG system development, vector databases, and embedding techniques. - Solid MLOps background: Docker, Kubernetes, CI/CD, model monitoring (Prometheus, Grafana), and automation. - Strong proficiency in Python and relevant ML libraries. - Experience deploying models to edge devices (e.g., Jetson, ARM). - Expertise in model optimization techniques (quantization, pruning, mixed precision) and performance tuning. - Familiarity with cloud and hybrid infrastructure (AWS, Azure, GCP). Desirable Qualifications: - Experience in regulated or security-sensitive environments with knowledge of data privacy, secure AI deployment, and governance. - Familiarity with tools for model monitoring, drift detection, and explainability. - Background in AI R&D or productization of machine learning systems in industry. Key Competencies: - Strategic thinking and hands-on execution - Technical leadership and team mentorship - Strong cross-functional communication - Problem-solving and delivery under tight timelines - Commitment to high-quality, reproducible AI development Performance Metrics: - Time to production for POCs and models - SLA-based model performance (accuracy, latency, uptime) - Inference cost reduction and throughput gains - Successful documentation and deployment handover - Edge rollout success and reliability Working Conditions and Benefits: - Fast-paced, multidisciplinary R&D environment - Competitive compensation and benefits - Professional development allowance - Opportunities to lead and shape strategic AI initiatives

About the company
Inspire Selection is an award winning recruitment agency, headquartered in Dubai which recruits across the Middle East region. We employ highly knowledgeable, professional consultants who are experts in connecting the right people with the right opportunities. Our reputation has been built upon our honesty, integrity and our ability to source candidates of the highest calibre right across our specialist sectors. As a result, we are recruitment partners to a wide spectrum of organisations - from leading blue chip companies to smaller, local businesses. Sectors we cover include HR, Administration, Finance & Accounting, Legal, Sales & Marketing including Digital Marketing, IT, Oil/Gas/Energy, Engineering, Procurement, Manufacturing, Higher Education.

Agentic AI Engineer - temp

Dubai, United Arab Emirates | Posted on 09/30/2025

AgenticAI Automation Engineer - Internal Tooling & AI Temp 6 months contract MeetmyZoi

myZoi is changing lives for the better for those who serve it the most. We are an exciting fintech start‑up aiming to promote financial inclusion globally. Our vision is to provide a level playing field to the unbanked and the underbanked in accessing essential financial services in an affordable, convenient, and transparent fashion. We are looking for smart, ambitious, and purpose‑driven individuals to join us in this journey.

About the Role

As the Agentic AI Engineer you will drive internal productivity through agentic AI orchestration and intelligent automation of business processes. Architect, develop, and deploy production‑grade autonomous agent systems that execute multi‑step workflows with minimal human intervention, streamlining operations across business, technology, operations, compliance, and risk functions while maintaining compliance in our regulated fintech environment. You'll work with AWS and the Atlassian ecosystem to create multi‑agent workflows that augment human decision‑making and automate manual processes end‑to‑end. As part of our Platform Team comprising Data Analysts, Data Engineers, and AI Specialists, you'll implement scalable, secure AI solutions that empower every employee, team, and process.

Key Responsibilities AI Agent Design & Development

• Design and deploy intelligent agents for multi‑step, autonomous workflows.
• Implement reasoning, memory, and decision‑making in agent orchestration.
• Develop reusable templates and agent patterns for common automation use cases.
• Integrate human‑in‑the‑loop and feedback mechanisms where needed.

Agent Frameworks & Orchestration

• Build with frameworks like LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel.
• Extend framework capabilities with custom agent components.
• Implement task delegation, coordination, and version control for agent behavior.

RAG & Knowledge Integration

• Optimize chunking, embedding, and search strategies using vector DBs (e.g., Pinecone, Weaviate).
• Integrate enterprise knowledge from Jira, Confluence, documentation, and more.

Tool & API Integration

• Enable agents to interact with AWS, Atlassian Cloud, and internal APIs.
• Build tool interfaces for agents to query databases, perform actions, and access services securely.

Multi‑Agent Systems

• Orchestrate collaborative agents (e.g., planner, executor, reviewer) to handle complex workflows.
• Design communication protocols, routing logic, and error handling strategies.

Performance, Monitoring & Optimization

• Monitor agents using tools like LangSmith, CloudWatch, custom dashboards.
• Debug behavior (hallucinations, latency, token usage) and run A/B tests for optimization.
• Ensure secure, scalable, and cost‑effective operation at production scale.

Production Deployment (AWS)

• Deploy AI agents using AWS Bedrock, Lambda, Step Functions, EventBridge.
• Build CI/CD pipelines, implement rollback strategies, and handle concurrency at scale.
• Ensure compliance, governance, and security across automation flows.

Atlassian Ecosystem Automation

• Develop Forge apps with embedded agent capabilities.
• Build agents to automate Jira workflows, incident triage, ticket routing, and Confluence content generation.
• Configure Atlassian Rovo as a knowledge source for AI agents, maintain and continuously improve.
• Partner with cross‑functional teams to identify automation opportunities.
• Translate business needs into robust agentic solutions.
• Document best practices, templates, and reusable components.
• Mentor peers in agentic AI workflows and frameworks.

Required Skills & Qualifications Core Experience

• 4–6 years in software development with AI/ML focus.
• Proven success deploying agent‑based AI systems in production.
• Strong Python and TypeScript skills; familiarity with FastAPI, Flask, and Atlassian APIs.
• Hands‑on experience with LLMs, prompt engineering, and agent frameworks (LangChain, CrewAI, etc.).
• Deep understanding of RAG, vector search, embedding models, and retrieval optimization.
• Expertise in AWS (Bedrock, Lambda, Step Functions, S3, EventBridge).
• Familiarity with serverless, Docker, Terraform, and CI/CD pipelines.
• Solid experience in Jira, Confluence, Forge, Rovo, and Atlassian APIs.
• Strong experience in automation and workflow development in Atlassian Cloud.
• Strong problem‑solving and debugging skills.
• Excellent communication and cross‑functional collaboration.
• Familiarity with DevSecOps, observability, and ethical AI practices.
• Experience with multi‑agent orchestration patterns (e.g., planner‑worker, chain‑of‑thought, reflection) nice to have.
• Familiarity with human‑in‑the‑loop and agent evaluation frameworks nice to have.
• Exposure to MLOps, multi‑modal AI, and cross‑platform cloud development nice to have.
• Experience with Kubernetes, graph databases, and event‑driven architecture nice to have.

What We Offer

• Opportunity to make a global impact by improving financial access for underserved populations.
• Collaborative, inclusive work environment that values diverse perspectives.
• Cutting‑edge work with latest agentic AI technologies, frameworks, and best practices.
• Competitive compensation and benefits package.
• Professional growth and development opportunities.

At myZoi we strive to create both a product and a team that embraces equality, inclusion, diversity, and freedom. We want people who can be themselves and bring their own brand of value to the team. Come and join us! #J-18808-Ljbffr

Overview

Job Title: Data & AI Engineer

Job Type: Full-Time

Location: Onsite - Sharjah, UAE

Job Summary:

Join our team as a Data & AI Engineer and become an integral part of a forward-thinking organization in the education and research sector. You will architect robust and scalable data and AI solutions, driving innovation through advanced data engineering and end-to-end machine learning in a government setting. This role values written communication and thrives in an asynchronous, highly collaborative environment.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines using Python, SQL, and orchestration tools such as Airflow, Talend, or Spark.
• Develop, deploy, and maintain machine learning models, implementing MLOps best practices for model versioning, monitoring, and retraining.
• Manage and scale cloud-based data and AI infrastructure, optimizing storage, compute resources, and performance for large-scale analytics.
• Ensure robust data governance and compliance, integrating regulatory requirements such as GDPR across data workflows and AI models.
• Integrate third-party APIs, automate complex data workflows, and support backend data structures for business intelligence and analysis.
• Collaborate cross-functionally to analyze trends, engineer features, and translate data insights for technical and non-technical audiences.
• Document pipelines, model architectures, and metadata while diagnosing and resolving technical issues with a root-cause approach.

Qualifications

• Advanced programming in Python, especially for data engineering and machine learning.
• Deep proficiency in SQL and hands-on experience with relational (MySQL, PostgreSQL) and non-relational (MongoDB) databases.
• Expertise with cloud-based data tools (Azure Data Factory, AWS) and ETL/ELT pipeline development.
• Proven ability with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and HuggingFace.
• Hands-on experience applying MLOps principles for model lifecycle management.
• Strong understanding of orchestration tools like Apache Airflow.
• Excellent written communication skills, vital for asynchronous collaboration.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or related field.
• Minimum 7 years' experience in data engineering, AI, or advanced analytics, with at least 2 years on AI/ML projects.

Preferred Qualifications

• Background in responsible AI, bias detection, and model explainability.
• Experience with data governance, compliance frameworks, and explainable AI (XAI).
• Exposure to advanced cloud-based AI orchestration and emerging ML technologies.

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Lab49 is an NYC-based award-winning global specialist consultancy thatcreates bespoke technology.

Lab49 is hiring aLead AI Engineerfor an exciting opportunity in one of the world's most dynamic business hubs.This is a chance to join a pioneering team that is setting new benchmarks in the use of agentic AI, prompt-driven UIs, and LLM-powered services for a high-impact B2C client in Dubai.

JOB SUMMARY:

As a Lead AI Engineer, you will play a pivotal role in the design and implementation of a complex, agentic AI–based solution for a major B2C company in Dubai, a market leader in its sector.

The platform will deliver omni-channel, prompt-driven AI services, leveraging LLMs, agentic orchestration, retrieval-augmented generation (RAG), and tight integration with the client’s existing digital and enterprise systems.

You will lead architectural decisions, guide development standards, and help shape the next-generation customer experience powered by intelligent, modular agents.

KEY RESPONSIBILITIES:

• Solution Design:
• Drive the architecture and solution design for the AI platform, ensuring it meets business, performance, and scalability requirements
• Design patterns for prompt-driven UI generation, long-term memory usage, and multi-agent collaboration
• Select appropriate frameworks and orchestrators (e.g., LangChain, LangGraph, CrewAI, Agno) based on project needs

• Application Development:
• Build and maintain production-grade agentic AI services in Python
• Own integration patterns between schema-rendered UI, prompt handling, and inference pipelines
• Implement APIs and backend components to interface with LLMs, memory stores, external tools, and enterprise systems
• Develop and integrate RAG pipelines, vector stores, and structured output parsing
• Contribute to re-usable libraries and accelerators
• Write clean, testable code and ensure robust CI/CD and deployment pipelines are in place

• Technical Leadership:
• Provide technical guidance to junior and mid-level developers
• Conduct code reviews and maintaining high standards of software quality
• Collaborate closely with product managers, front-end developers, and Lab49’s and Client’s architecture and QA teams
• Stay current with the rapidly evolving LLM landscape and proactively suggest innovations

EXPERIENCE AND SKILLS:

• Required experience and skills:
• Bachelor's degree in Computer Science, Information Technology, or a related field. Master’s degree is preferred
• 5 to 10 years of hands-on software engineering experience
• Strong expertise in Python and modern backend development practices
• At least 2 years implementing LLM and Agentic AI solutions
• Proven delivery of production-grade conversational AI platforms or prompt-native experiences (e.g., chatbots, voice assistants, agentic workflows)
• Solid understanding of cloud-native AI services, preferably on AWS
• Experience working in an agile, product-oriented delivery environment

• Desired experience and skills:
• Experience with RAG architectures, information extraction, and vector databases is desirable
• Experience with Agno is a strong plus.

*Details of the hybrid model: theteam normally meets for 2 days a week in the office, client work may require more presence on the client premises, especially during the integration, testing and release phases of a project

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As a Full-Stack + AI Engineer , you’ll own verticals from UI to backend to AI pipelines . You’ll

be at the core of how users talk to BOTty, get suggestions, and trust automation.

Frontend

Desktop/Cloud/AR mobile interface for fallback control

Secure web portal for automation editing, logs, and remote access

Explainability UI: “Why did BOTty do this?”

Backend

Local-first backend for event logs, ZeroConf device discovery, and API routing

Authenticated SSL tunnel gateway (no cloud relay)Real-time routines, preferences, and presence tracking

AI & Automation

Build and fine-tune agentic routines (Learn → Observe → Adapt → React)

On-device ML for micropatterns, low-latency NLU, and safety checks

Personalization ledger, feedback loops, and bandit-style decision tuning

Our Stack

Frontend:  React, Lit, Next.js, Tailwind, Shadcn UI

Backend:  Python, FastAPI, Node.js, SQLite, PostgreSQL, Mongo DB, TLS tunnels

AI:  CrewAI, LangChain, LlamaIndex, ONNX, OpenAI API

Infra:  RPi 5, Jetson, Cloud

DevOps:  Docker, DevContainers, GitHub Actions, OTA modules, local-only CI

RequirementsOur Stack

Frontend:  React, Lit, Next.js, Tailwind, Shadcn UI

Backend:  Python, FastAPI, Node.js, SQLite, PostgreSQL, Mongo DB, TLS tunnels

AI:  CrewAI, LangChain, LlamaIndex, ONNX, OpenAI API

Infra:  RPi 5, Jetson, Cloud

DevOps:  Docker, DevContainers, GitHub Actions, OTA modules, local-only CI

Have built and shipped agentic AI apps , ML-driven products, or full-stack SaaSLove debugging both frontend microinteractions  and low-level sensor events Are comfortable working on hardware like Jetson/RPi , or eager to learnEnjoy working across disciplines — AI, UX, home automation, privacyCan take vague product ideas and make them real, fast Bonus if You… Won or placed in hackathons Built your own SaaS product(s) or dev toolsKnow Zigbee, BLE, Matter, or embedded LinuxHave contributed to open-source AI or Web3 projectsEnjoy voice UX, reactive UI, or agent architecturesBenefitsCompetitive compensation + equity Work directly with founding team on product 0 → 1Build something with lasting impact, privacy-firstFast-paced, respectful, async-friendly team culture

**Job Description:**
DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business - today and in the future.
As an AI Engineer on our Professional Services team, you will be at the forefront of the AI revolution, working directly with our most strategic customers. You'll be a trusted advisor and hands-on builder, translating complex business challenges into cutting-edge AI solutions that deliver tangible business value.
This is a unique opportunity to design, build, and deploy a wide range of applications-from powerful predictive models to sophisticated Generative AI agents and chatbots. If you thrive on solving real-world problems and want to work with the latest in AI technology, this role is for you.
This role is based in Dubai, United Arab Emirates.
**This is a fully remote position with no requirement to go into an office on a regular basis. There will be travel requirements associated with this position to visit clients onsite up to 25% - 50% of the time.**
**Key Responsibilities:**
+ Partner with Customers: Collaborate closely with customer stakeholders to understand their business goals, identify high-impact use cases, and define technical requirements for AI solutions.
+ Build & Deploy AI Solutions: Design, develop, and deploy end-to-end AI solutions using the DataRobot platform and open-source tools. This includes:
+ Agentic AI: Developing and deploying agents on DataRobot leveraging common frameworks such as Langgraph, CrewAI, Llama Index
+ Generative AI: Building custom GenAI chatbots, Retrieval-Augmented Generation (RAG) systems.
+ Predictive AI: Developing and deploying classic machine learning models for use cases like forecasting, churn prediction, and fraud detection.
+ Serve as a Technical Expert: Act as a subject matter expert on the DataRobot platform and modern AI/ML development, guiding customers on best practices for MLOps, model governance, and scaling AI initiatives.
+ Deliver Value: Ensure that the solutions you build are robust, scalable, and directly contribute to the customer's business objectives.
+ Communicate & Collaborate: Clearly communicate complex technical concepts and project outcomes to both technical and non-technical audiences, from data scientists to C-level executives.
**Knowledge, Skills and Abilities** **:**
**AI & Machine Learning Expertise:**
+ Strong proficiency in Python and common data science libraries (e.g., pandas, scikit-learn, NumPy, etc.).
+ Practical experience with Generative AI technologies, including Large Language Models (LLMs), vector databases,
+ Solid understanding of the end-to-end agentic AI lifecycle from building agents in frameworks like LangGraph or CrewAI, to at scale deployment and monitoring.
**Application Development & Operations:**
+ Demonstrable experience developing and deploying applications, including building REST APIs (e.g., using Flask, FastAPI) to serve ML models and GenAI logic.
+ Proficiency with containerization using Docker and experience deploying and managing applications on container orchestration platforms like Kubernetes (K8s).
+ Solid understanding of secure application development practices, including authentication/authorization (e.g., OAuth, API keys), secrets management, and securing public-facing endpoints.
+ Customer Focus: Experience in a client-facing or consulting role with exceptional verbal and written communication skills. You must be comfortable leading technical discussions and presenting to diverse audiences.
+ Problem-Solving Mindset: A deep curiosity and a passion for solving complex, unstructured problems.
**Requisite Education and Experience / Minimum Qualifications:**
+ Experience: Approximately 6-8 years of hands-on experience in AI Application development, software engineering, machine learning engineering, or a similar role with a proven track record of deploying AI solutions or applications into production.
+ Education: A Master's Degree or Ph.D. in Computer Science, Statistics, Artificial Intelligence, Engineering, or a related quantitative field.
+ Cloud Experience: Hands-on experience with a major cloud platform (AWS, Azure, or GCP).
+ DataRobot Experience: Familiarity with the DataRobot AI Platform is a strong plus.
+ MLOps Knowledge: Understanding of MLOps principles and tools for model CI/CD, monitoring, and governance.
+ Fluency in English and Arabic
+ Willingness to travel onsite with clients up to 40% of the time
The talent and dedication of our employees are at the core of DataRobot's journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees' well-being at the core. Here's what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more!
**DataRobot Operating Principles:**
+ Wow Our Customers
+ Set High Standards
+ Be Better Than Yesterday
+ Be Rigorous
+ Assume Positive Intent
+ Have the Tough Conversations
+ Be Better Together
+ Debate, Decide, Commit
+ Deliver Results
+ Overcommunicate
Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. **At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box.** We'd love to have a conversation with you and see if you might be a great fit.
DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.
All applicant data submitted is handled in accordance with our Applicant Privacy Policy ( .
DataRobot delivers AI that maximizes impact and minimizes business risk. Our AI applications and platform integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business - today and in the future. For more information, visit our website ( and connect with us on LinkedIn ( .
**_DataRobot has become aware of scams involving false offers of DataRobot employment. The scams and false offers use imposter websites, email addresses, text messages, and other fraudulent means. None of these offers are legitimate, and DataRobot's recruiting process never involves conducting interviews via instant messages, nor requires candidates to purchase products or services, or to process payments on our behalf._** **_Please note that DataRobot does not ask for money in its recruitment process._** **_DataRobot is committed to providing a safe and secure environment for all job applicants. We encourage all job seekers to be vigilant and protect themselves against recruitment scams by verifying the legitimacy of any job offer before providing personal information or paying any_** **_fees. Communication_** **_from our company will be sent from a verified email address using the @_** **_datarobot.com_** **_email domain. If you receive any suspicious emails or messages claiming to be from DataRobot, please do not respond._**
**_Thank you for your interest in DataRobot, and we look forward to receiving your application through our official channels._**
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