Seeking a Senior Gen AI & Data Science Engineer to design, build, and productionize AI solutions on Microsoft Azure, focusing on Azure OpenAI and the broader AI stack. This hands-on role requires proven experience in delivering real-world GenAI/RAG/analytics projects, particularly within financial services.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
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:
- Azure services used
- LLM / model used
- Your exact role
- 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.
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