About the Role

We are looking for a senior Gen AI & Data Science Engineer who can design, build, and productionize AI solutions on Microsoft Azure — especially using Azure OpenAI and the broader Azure AI stack. This is a hands-on, solution-building role for someone who has already delivered real-world GenAI / RAG / analytics projects.

Key Responsibilities

• Architect and implement GenAI applications using Azure OpenAI (GPT, embeddings, assistants) and Azure AI Foundry.
• Design and optimize RAG (Retrieval-Augmented Generation) pipelines: document ingestion, text/vector embeddings, chunking strategies, metadata, hybrid search, evaluation.
• Work with vector databases (e.g. Azure AI Search, Redis, PostgreSQL with pgvector, Milvus, Pinecone) and implement vectorization of text and semi-structured data.
• Build and orchestrate agentic workflows using frameworks like LangChain, Crew.AI, A2A or equivalent to support multi-step, tool-using AI agents.
• Develop and deploy predictive analytics and ML models (classification, regression, time series, anomaly detection) aligned to FS use cases (KYC/AML, collections, underwriting, RoI modeling, pricing, customer insight).
• Package solutions as APIs / microservices for consumption by business apps, portals, or channels.
• Define MLOps / AIOps practices on Azure (CI/CD, model registry, monitoring, drift, evaluation).
• Work closely with business stakeholders to translate requirements into data/AI products.
• Ensure security, governance, and data privacy compliance for financial services workloads.

Skills & Qualifications

• 7-10 years of experience in Data Science / ML / AI engineering roles.
• European nationality (EU passport) — for mobility / customer/regulatory reasons.
• Strong, recent hands-on experience with Azure OpenAI and Azure AI services (AI Foundry / AI Search / Cognitive Services).
• Proven experience in building RAG systems end-to-end (data prep → embedding → retrieval → prompt orchestration → evaluation).
• Solid understanding of embeddings and vector similarity search (cosine / dot product / hybrid).
• Practical experience with LangChain or similar chain-of-thought / tool-calling frameworks.
• Hands-on with agentic frameworks (Crew.AI, A2A, AutoGen, etc.) for multi-agent task execution.
• Excellent Python skills (pandas, PyTorch/TF/sklearn, FastAPI).
• Experience in financial services data models and processes.
• Strong architecture mindset: can choose the right Azure service for the problem.
• Very good English communication; able to present to non-technical stakeholders.

Why join us

• Work with a pragmatic, execution-focused team that values quality over shortcuts.
• Autonomy to choose the right tools/architectures and set engineering standards.
• Build category-defining AI systems for high-impact financial use cases

How to Apply:

Please share your CV + 3 project examples (GenAI / RAG / FS ML) that you delivered in the last 24 months. Highlight:

1. Azure services used
2. LLM / model used
3. Your exact role
4. Outcome / business value

Submit your CV and a brief cover letter outlining your experience at [email protected].

All relocation and Qatar residency assistance will be provided.