Job Title - Gen AI Lead
Location - Beerse, Belgium
Duration - 6 Months contract
100% Onsite role at Beerse, Belgium
- Must have 10+ years of experience. Mostly in Data science, AI ML, GenAI and NLP technologies.
- At least 2+ years in GenAI application development
- Experts in problem solving, developing technical solutions
- Must have experience with Agentic AI frameworks – LangGraph, LlamaIndex, Function calling, Chain of thoughts, MCP, Tools register, intent based routing etc.
- Expert in using paid (OpenAI on Azure, Bedrock in AWS, other leading one) and open source LLMs, VLM, SLM etc
- Expert in RAG, CAG, Knowledge Graph RAG, RAG Fusion, Agents, MCP, NLQ to SQL etc.
- Experience in handling large unstructured (multiple file formats) and structured (data Lake) data
- Experience with multiple leading Vector DB, chunking strategies, Graph DB (Neo4J)
- DAR for applying best solution for problem statements
- Experience in multi Agents system development, Agentic AI
- Experience with Python programming language. Should know other languages too
- Ability to develop Python code efficiently, FastAPI
- Solid understanding of Model development, model serving, training/re-training techniques in a data sparse environment.
- Enforce reusable component development and sharing across solutions
- Experience with AWS / Azure ecosystem and development accordingly is a must. Kubernetes and other server less deployments
- Very good understanding of Prompt engineering techniques in developing Instruction based LLMs.
- Work with SAs and collaborate with cross-functional teams to identify business requirements and deliver solutions that meet the customer needs.
- Passionate to learn and stay updated with the latest advancements specially in generative AI and LLM.
- Ability to articulate to business stakeholders on the hallucination effects and various model behavioral analysis techniques followed.
- Experience developing Guardrails for LLMs both with open source and cloud native models.
- Collaborate with software engineers to deploy and optimize generative models in production environments, considering factors such as scalability, efficiency, and real-time performance.
- Experience in RDBMS database, Data Lake, Postgresql
- Experience on Marklogic / No SQL database
- Experience on Elastic search