Your AI career in the UAE starts here

Position: Lead Generative AI Implementation – Full Stack | Azure AI FoundryLocation: Abu Dhabi, UAEWork Model: 100% OnsiteExperience: 10+ yearsEmployment Type: Full-timeWe are hiring on behalf of a UAE Government Department for a hands-on Generative AI Implementation Lead to join its AI team in Abu Dhabi.The ideal candidate will combine strong implementation of Generative AI/LLM expertise with full-stack software engineering and Microsoft Azure experience and will be responsible for building and deploying production-ready AI applications.Key ResponsibilitiesLead the team, implement and develop Generative AI applications, AI assistants, copilots, and agentic AI solutions. Build and optimize RAG pipelines, AI agents, embeddings, semantic search, and LLM integrations. Develop full-stack AI applications across frontend, backend, APIs, databases, and AI orchestration layers. Integrate AI solutions with enterprise systems, APIs, and databases. Deploy and manage AI applications using Microsoft Azure, Docker, CI/CD, and modern cloud practices. Build scalable, secure, and production-ready AI solutions with appropriate monitoring and evaluation. Rapidly prototype AI solutions and convert successful concepts into production applications. Work with business and technical stakeholders to identify and implement practical AI use cases. Required SkillsStrong hands-on experience with Implementation of Generative AI / LLM applications. Strong Python programming skills. JavaScript / TypeScript and experience with React, Next.js, Node.js, FastAPI, Flask, or equivalent technologies. Experience with RAG, embeddings, vector databases, AI agents, prompt/context engineering and LLM APIs. Experience with Microsoft Azure and cloud-based application deployment. REST APIs, Git, Docker and CI/CD. Familiarity with AI development tools such as Cursor, GitHub Copilot, Claude Code, Codex, Windsurf, or similar. Strong software engineering and problem-solving skills. Nice To HaveExperience with Azure AI Foundry, Azure AI Search, Azure Machine Learning, LangChain, LangGraph, LlamaIndex, Semantic Kernel, MLflow, Kubernetes, or LLM serving technologies will be an advantage.QualificationsBachelor's degree in Computer Science, AI, Data Science, Software Engineering, Computer Engineering, or a related field. 10+ years of relevant experience in AI Engineering, Generative AI, Software Engineering, ML, Data Science, or Applied AI. A strong portfolio of AI applications/projects is highly desirable. Important – Location:📍 This is a 100% onsite role based in Abu Dhabi.Candidates must either be currently based in Abu Dhabi or be willing to relocate to Abu Dhabi from another emirate.Please note: No relocation allowance, relocation package, or family relocation assistance will be provided.If you are a hands-on GenAI Implementation Engineer who can lead, build, code, integrate, and deploy AI applications, we'd like to hear from you.Skills: rag,semantic kernel,vector databases,autogpt,agents,agentic ai,prompt engineering,azure,langchain,llama2,generative ai,crewai,embedding models,ai application development,llm frameworks,gemini,openai

10+ years in software development, 5+ years hands-on AI, and having led at least 2 technology/AI delivery projectsBuild LLM-based AI agents for market intelligence generation.Develop retrieval and vector search capabilities using PostgreSQL / pgvector.Implement context management and multi-agent orchestration.Develop FastAPI services for seamless front-end integration.Build conversational agent workflows with evidence-grounded generation.Implement evaluation, numeric verification, sourcing and compliance checks.Support Azure deployment, CI/CD, monitoring and documentation.Required skills: Python, FastAPI, LLM/Agentic AI development, RAG, vector search, PostgreSQL/pgvector.Also required: agent orchestration, context management, AI evaluation and observability, Azure and CI/CD.

Nabat is a climate-tech startup based in the UAE using advanced technology to protect and restore natural ecosystems with precision and scale! We operate at the intersection of ecological & environmental sciences, GIS, AI, and robotics. Our mission is to enable data-driven, science-backed ecosystem management and restoration at the speed and scale necessary to address the critical challenges of climate change, deforestation, land erosion, and biodiversity loss. Our comprehensive solution - consisting of ecosystem management software, precision aerial seeding drones, AI & ecological models, and restoration services - is already being used to plant millions of mangroves in the UAE. But we’re just getting started, as we build our platform to serve the needs of coastal, marine and arid ecosystems around the world.If this mission resonates with you, let’s talk.What is the role?We’re building our product development team from the ground up and are looking for highly talented, self-driven Senior Data Scientists with proven experience using cutting-edge data science techniques to extract science-backed insights from large, complex geospatial data sets.Your Responsibilities Will IncludeAct as senior/staff-level individual contributor to own the development of analytical and predictive models for Nabat’s AI-powered ecosystem management platform, using a variety of AI/ML and statistical techniques. Research, develop, train, validate, refine and deploy models that use deep domain knowledge to extract user-friendly scientific and ecological insights from geospatial data. Some of the problems you might be working on using satellite and drone imagery: land use/cover classification identification of plant native and invasive species estimating carbon stock and biodiversity modeling and predicting the outcome of different restoration scenarios creating optimal flight paths for multi-drone seeding operations detecting ecosystems at risk measuring plant-level growth metrics high-throughput phenotyping, and so on. In close collaboration with software and data engineers, design and implement well-architected, scalable, robust, high-performance, AI/ML-powered systems for ingestion, storage, processing, analysis, insight extraction, and visualization of large amounts of geospatial time-series data (geotagged, ultra-high-resolution RGB, multi- and hyper-spectral imagery, KML files, LIDAR point clouds, etc from satellites and drones) Communicate and collaborate cross-functionally with product managers, software, hardware and data engineers, ecologists, GIS data analysts, drone pilots, operations folks, and end users to deliver key initiatives Knowledge transfer from and continuous engagement with researchers (from Technology Innovation Institute) and external partners to understand and take ownership what has been built to date, become the subject matter expert for your product domain, and lead the research & development roadmap for your domain What are we looking for?A strong research/academic foundation with at least a Masters degree in engineering, data science, mathematics, ecological or environmental science, or similar fields, and ideally published research in peer-reviewed journals. Extensive, hands-on development experience with AI/ML model development in the geospatial, computer vision and/or remote sensing domain, including Familiarity with the latest machine learning techniques and models for image analysis, object detection, semantic segmentation, pattern recognition, predicting outcomes, anomaly detection, or similar using large geospatial datasets (RGB, multi- and hyper-spectral drone imagery, LIDAR point clouds, satellite imagery, etc) Experience combining data from multiple sources (sensor fusion) such as drones, satellites, ground truth, in field sensors or from multiple models (ensemble methods) to improve performance Researching appropriate models and techniques given a problem space, scientific and business context, and validating different options before recommending a solution Experience using supervised and unsupervised learning, deep learning, CNNs, RNNs, GANs, and the like in the geospatial domain Determining quantifiable measures for the quality of data and performance of models, evaluating and communicating these metrics to stakeholders Using geospatial data processing, analysis, and visualization tools (Python, R, PyTorch, Jupyter, QGIS, Grass GIS, ArcGIS, etc) Experience performing self-directed exploratory data analysis using statistical and visualization tools to understand patterns, trends, and anomalies and present results Experience working with and deploying production-ready models to cloud platforms: AWS, GCP, or Azure Experience working with software engineers, data engineers and GIS data analysts to productize and launch models to production Builder/entrepreneur mindset: You've created something meaningful from the ground up - whether leading a project, founding a venture, or crafting an impressive side project that demonstrates your initiative. Communication excellence: You articulate ideas clearly and document thoroughly, understanding that transparent communication is fundamental to our collaborative approach. Bias for action and execution: You move with purpose and velocity, driving for impact rather than perfection. You're comfortable making decisions and failing fast when necessary to achieve results. You prioritize shipping and iterating over endless conceptualizing. Problem-solving aptitude: You approach challenges with creativity and pragmatism, finding elegant solutions that balance technical constraints with user needs. Nice to haves: previous experience building products in the domain of geospatial AI, remote sensing, earth observation, environmental monitoring, precision agriculture, or drone robotics Why join Nabat?A once-in-a-lifetime opportunity toJoin a well-funded early-stage tech startup at the intersection of some of the most exciting, disruptive and innovative technologies in the world - geospatial AI, remote sensing, drone robotics, ecology & agricultural science Design, build and shape a product from the ground up using your unique skills and expertise Work with a truly international and world-class R&D team both within Nabat and in collaboration with 1200+ researchers, scientists and technologists in the larger Advanced Technology Research Council (https://www.atrc.gov.ae/), Technology Innovation Institute (https://www.tii.ae/), and VentureOne (https://www.ventureone.ae/) ecosystem. Relocate to Abu Dhabi – one of the safest, most livable, expat-friendly cities in the world - with an “all inclusive” relocation package for you and your family, that includes work & residence visa sponsorship, relocation flights, orientation tour, school and house search, and hotel stay until you find your new home Make a real and direct impact to solving the most critical challenges of our time – climate change and ecosystem loss! What is the hiring process like?We believe in making your hiring and onboarding seamless and transparent. Here is what to expect from us:Initial screening call with a member of our Talent team to ensure expectations and experience aligns First interview with hiring manager about the role and ask questions – Taha Ghaznavi, Chief Product Officer, Nabat Second interview with technical team member(s) to assess your capabilities. Might include a coding test and/or small case study. Third interview with a senior leader to assess culture fit and give you opportunity to meet your future stakeholders Security clearance and final offer Relocation to the UAE and onboarding! Apply with your CV and tell us what makes you & your experience a great fit for Nabat.How To ApplyAre you ready to embark on an exciting journey with Nabat? To apply, please send your resume detailing your relevant experience and why you're the perfect fit for this role.At Nabat, we’re not just building technology — we’re shaping the future of sustainable agriculture through innovation and collaboration. If you’re passionate about making a real-world impact and working alongside a diverse team of curious minds, we’d love to hear from you. Join us in transforming data into solutions that matter.

About usVentureOne is not just a company; it is an innovation hub, a hotbed of creativity, and a place where groundbreaking ideas become reality. Our team is a diverse mix of visionaries, strategists, and go-getters, all united by a shared mission: to redefine industries and pave the way for success, both locally and globally.About the roleWe are looking for a Senior AI Engineer to join the VentureOne Foundry team. This team explores new venture ideas, builds working MVPs, validates them with customers, and helps create new products across different domains.This is a hands on technical leadership role for an AI engineer who can design, build, evaluate, and scale applied AI systems. The Senior AI Engineer will lead the development of AI enabled products, including LLM applications, RAG systems, AI agents, workflow automation, copilots, document intelligence, evaluation frameworks, and AI powered decision support tools.The role requires strong AI engineering, strong software engineering judgment, product thinking, and the ability to build systems that are useful, measurable, safe, reliable, and ready for customer validation.Key Responsibilities:Lead the design and development of AI enabled products from early concept to MVP, customer validation, and early production readiness.Translate ambiguous business problems into AI solution designs, experiments, architecture diagrams, evaluation plans, and working systems.Design and build LLM based applications using commercial and open source models through APIs, hosted inference, or private deployments.Build RAG systems including document ingestion, parsing, chunking, embeddings, vector search, hybrid search, reranking, citation generation, access control, and answer evaluation.Build AI agents and tool calling workflows that can use APIs, databases, search, documents, business rules, and human review steps.Design orchestration patterns for multi step AI workflows, including planning, tool execution, guardrails, retries, fallback paths, state management, and traceability.Build AI evaluation pipelines using golden datasets, test cases, automated checks, human review, quality scoring, regression testing, and failure analysis.Evaluate model quality, prompt performance, retrieval accuracy, hallucination rate, latency, cost, reliability, safety, and user experience.Design AI systems with human oversight, auditability, traceability, permissions, data privacy, and clear failure handling.Work with structured and unstructured data, including PDFs, images, forms, emails, transcripts, logs, knowledge bases, and enterprise records.Partner with Senior Full Stack Engineers to integrate AI capabilities into complete products, APIs, dashboards, workflows, and customer facing experiences.Build reusable AI components such as prompt templates, agent patterns, evaluation harnesses, model gateways, retrieval services, and reference architectures.Identify and manage AI risks including hallucination, prompt injection, data leakage, unsafe outputs, retrieval errors, model drift, cost spikes, and poor user trust.Document AI architecture, assumptions, limitations, evaluation results, risk controls, and operational requirements.Stay close to AI industry developments and convert relevant ideas into practical product opportunities for VentureOne.Contribute to hiring, technical assessment, mentoring, and AI capability building for the Foundry team.Minimum Qualifications:Strong experience building applied AI products, LLM based applications, AI platforms, or machine learning systems.Proven ability to lead technical direction for AI systems in complex and ambiguous environments.Hands on experience with LLMs, prompt design, embeddings, vector databases, RAG, model APIs, structured outputs, and AI orchestration.Experience building AI agents, tool calling workflows, function calling, workflow automation, or AI powered business processes.Strong programming experience in Python and strong understanding of production software engineering practices.Experience with AI frameworks and libraries such as LangChain, LlamaIndex, Semantic Kernel, Haystack, AutoGen, CrewAI, Flowise, or similar tools.Experience with vector stores and search systems such as pgvector, Pinecone, Weaviate, Qdrant, Elasticsearch, OpenSearch, Azure AI Search, or similar platforms.Experience designing ingestion pipelines for documents, text, tables, metadata, permissions, and enterprise knowledge sources.Experience evaluating AI systems using structured test sets, quality metrics, automated evaluation, human review, benchmark based approaches, or production feedback loops.Good understanding of APIs, back end services, data pipelines, cloud deployment, observability, logging, tracing, and system integration.Strong understanding of AI safety, responsible AI, privacy, security, prompt injection defense, data leakage prevention, and operational failure modes.Ability to optimize AI systems for cost, latency, quality, reliability, and scalability.Ability to move quickly from idea to prototype while maintaining clear thinking about evaluation and production readiness.Strong communication skills with the ability to explain AI behavior, limitations, risks, and tradeoffs to technical and non technical stakeholders.Preferred Qualifications:Experience with agentic systems, AI workflow builders, orchestration platforms, multi agent systems, or AI control planes.Experience with cloud AI services on AWS, Azure, GCP, or private cloud environments.Experience with model gateways, model routing, prompt versioning, prompt registries, experiment tracking, and AI observability.Experience with document intelligence, OCR, form extraction, classification, summarization, entity extraction, and knowledge graph enrichment.Experience with AI governance, audit trails, human oversight, model evaluation, policy controls, and responsible AI frameworks.Experience in regulated domains such as government, fintech, identity, real estate, health, or enterprise platforms.Experience building customer facing AI products, not only research prototypes.Experience creating reusable AI patterns, reusable prompts, agent templates, evaluation frameworks, and reference architectures.Experience deploying AI capabilities with security, tenant isolation, role based access, cost monitoring, and production monitoring.We provide a competitive, tax-free salary and a comprehensive benefits package in a collaborative, innovative and inclusive work environment. Our benefits include an education allowance, free on-site meals, annual flight allowance, health coverage, relocation support (if applicable), and access to well-being activities such as sports and recreational events.Join us to drive innovation and shape the future of technology!How to Apply:Are you ready to embark on an exciting journey with VentureOne? If you're a visionary with a passion for innovation, we want to hear from you. To apply, please send your resume detailing your relevant experience and why you're the perfect fit for this role.At VentureOne, we believe that diverse perspectives drive innovation. We are committed to creating an inclusive and equal opportunity workplace. All qualified applicants will receive equal consideration for employment. Join us in shaping the future of business. Apply today and let's venture into a world of possibilities together!Click to apply - Senior AI Engineer

AI Engineer – Multi-Agent SystemsLocation: Abu Dhabi, UAEAbout the RoleA private investment office in Abu Dhabi is expanding its elite technical team to build and own state-of-the-art multi-agent orchestration and agentic infrastructure. You will architect the core systems that enable autonomous AI agents to plan, execute tool calls, retry on failure, and reliably hand off complex workflows in production.Key ResponsibilitiesDesign and build scalable systems for task decomposition, inter-agent communication, and state management.Own sandboxing, guardrails, automated retries, fallback logic, and real-time observability.Build rigorous evaluation pipelines to catch performance regressions before production deployment.Architect reliable retrieval (RAG) and tool-use infrastructure across structured and unstructured data sources.What You BringDeep expertise building with advanced LLM architectures, RAG, agentic reasoning, and multi-agent workflows.A clear grasp of where standard agent frameworks (e.g., standard ReAct loops) break down, and how to engineer resilient workarounds.Background in financial services, investment management, fintech, or high-throughput engineering environments (advantageous).Active open-source contributions, AI research publications, or relevant patents are highly valued.Tech StackLangGraph, AutoGen, or custom agent frameworksModel Context Protocol (MCP), Vector Databases (Pinecone, Qdrant, Chroma, etc.), Hybrid SearchPython (PyTorch/TensorFlow, AsyncIO, FastAPI)Compensation & BenefitsHighly competitive, tax-free base salaryDiscretionary performance-based annual bonusFull visa sponsorship and premium relocation packageComprehensive private health insurance and dependent schooling allowancesHow to ApplyIf you want to build cutting-edge agentic infrastructure in a high-performance environment, apply now or reach out directly to Syed at syed@durlstonpartners.com.

Principal Forward Deployed Engineer - AI & Agentic SystemsAbout the RoleDomain Rewiring means redesigning the operational domain itself — workflows, decision points, data flows and human roles — so that agentic AI becomes embedded into how work actually gets done.The Forward Deployed Engineering team works directly inside government entities to identify, build and deploy these systems, ensuring the underlying AI platform is shaped by real operational requirements rather than developed in isolation.Why JoinWork on complex applied AI problems. Re-engineer live government workflows and deploy agentic AI where operational decisions are actually made.Own outcomes, not just engineering. Define the users, workflow, success metrics and scope, then take the solution through to production and adoption.Small, senior teams. Work in compact squads of experienced engineers with significant autonomy and direct access to senior government stakeholders.Build the practice. Help establish the playbook for evaluation, AI-native software development and forward deployment, before helping grow the team around it.UAE-based opportunity. Relocation assistance is available for successful candidates and their families.The RoleWe are hiring a Principal Forward Deployed Engineer to join a small team of senior engineers responsible for taking complex government domains from discovery through to production AI systems.This is an individual contributor role first.You will personally own some of the organisation’s most challenging domain rewirings, working directly with users and senior stakeholders to understand how an operation works today and redesign how it should operate in an AI-native environment.There is no traditional business analyst, product manager or architect sitting between you and the problem. You define the users, workflow, scope, success metric and value case — and then build.You will own domain rewiring, adoption and realised business value, while partnering with specialists across AI engineering, product engineering, platform architecture and evaluation.As the programme grows, you may also lead a rewiring pod, hire engineers or own part of the domain portfolio. However, leadership sits alongside hands-on delivery rather than replacing it.What You OwnEmbed and define. Work directly inside government entities, understand how operations actually run and define the requirements yourself. Establish the metric, capture the baseline and agree it with the business owner before building.Design and ship. Architect agentic workflows spanning orchestration, retrieval, tools, agents, evaluation and human-in-the-loop processes — then write the production code.Navigate enterprise constraints. Take deployments through security, privacy, tenant isolation, governance and information-security reviews, creating reusable patterns for future deployments.Own adoption. Redesign the human process alongside the software. Success means changing how decisions are made, reducing cycle times, lowering costs or improving measurable outcomes.Prove value. Instrument products so their impact can be measured against an agreed baseline. Recommend scaling, redesigning or stopping initiatives based on evidence.Make the next deployment faster. Convert lessons from individual rewirings into reusable platform capabilities, engineering patterns and playbooks.First Three MonthsIndicative outcomes include:Delivering one lighthouse domain rewiring end-to-end within a major government entity, reaching production and demonstrating measurable improvement.Establishing an agreed value case and baseline with the relevant business owner and delivering the first value report.Contributing reusable capabilities to the underlying sovereign AI platform based on requirements discovered through real-world deployment.Who You AreStrong production engineer.You have personally shipped software end-to-end. Years of experience matter less than what you have successfully put into production.Field-hardened.You thrive in ambiguous, embedded and stakeholder-facing environments where the problem has not yet been clearly defined.Hands-on with agentic AI.You have practical depth across LLM and agent systems, including orchestration, retrieval, evaluation, agent design and prompt engineering. AI coding tools are part of your normal development workflow.Product owner by instinct.You are comfortable interviewing users, defining requirements, prioritising problems and cutting scope without waiting for a Product Manager.Business literate.You can discuss cost, cycle time, productivity, headcount and ROI with senior executives without hiding behind technical terminology.Enterprise literate.You understand identity, networking, data governance, security and approval processes required to move software into production within complex organisations.Value disciplined.You are willing to stop, redesign or descope your own work when the evidence shows it will not create sufficient value.Strongly PreferredForward Deployed Engineering, Solutions Engineering or technical delivery experience.Experience building or leading an FDE capability.Delivery experience within government, financial services or another regulated/high-assurance environment.Founder, founding engineer or zero-to-one product experience.Hands-on cloud and platform engineering experience, particularly Azure.Arabic and English capability, or experience operating effectively within bilingual environments.Evidence We Will Ask ForWe will want to understand:Two products you personally built that reached real users in production, including your contribution, scale and measurable outcome.For at least one product, the baseline before deployment, measured result afterwards, how the impact was measured and who validated it.One product you stopped, redesigned or significantly descoped because the expected value did not materialise, including the evidence behind that decision.Projected benefits in a business case are not considered realised impact.How Performance Is MeasuredPerformance is based on three primary outcomes:Speed: Time from problem definition to a rewired workflow being used in production.Value: Measurable impact against an agreed baseline, validated by the relevant business owner.Judgement: Rewirings that successfully pass the value checkpoint — and initiatives correctly stopped early when the evidence does not support further investment.Performance is not measured by lines of code, number of pilots or size of team.What This Role Is NotNot a management role disguised as engineering.You may lead engineers or a portfolio, but you remain personally responsible for delivering rewirings.Not advisory.Recommendations that end with a presentation or strategy document do not count. You build and ship.Not a pilot factory.A portfolio of proofs of concept that never reaches production or creates measurable value is not considered successful.