Senior GenAI Engineer

We are seeking a Senior GenAI / RAG Engineer with strong experience in Generative AI, Retrieval-Augmented Generation (RAG), Azure, vector databases, and event-driven microservices experience building production-grade AI solutions in the Banking/Financial Services domain , preferably with AML/KYC use cases.

The candidate should be able to design, develop, and explain an end-to-end RAG architecture and understand how GenAI solutions integrate with existing deterministic systems such as AML rule engines.

Key Responsibilities

• Design and develop enterprise-grade RAG and Generative AI solutions for banking and financial services use cases.
• Build RAG pipelines covering document ingestion, chunking, embeddings, vector search, retrieval, reranking, prompt construction, and LLM response generation .
• Integrate RAG solutions with existing AML rule engines and investigation/case-management systems .
• Ensure RAG complements deterministic AML decisioning rather than duplicating or re-running existing business rules.
• Implement grounded responses with source citations, evidence retrieval, and hallucination mitigation .
• Work with Pinecone or similar vector databases for semantic search and retrieval.
• Use Azure Blob Storage for document/file storage and build document ingestion pipelines.
• Integrate Azure OpenAI/LLM services into enterprise applications.
• Design and develop scalable Python-based microservices and REST APIs .
• Work with Kafka topics, partitions, consumer groups, replication, ISR, offsets, retries, and fault-tolerant processing.
• Implement metadata filtering, similarity thresholds, document versioning, and relevance optimization within RAG pipelines.
• Collaborate with architects, developers, data engineers, product teams, and banking/AML subject matter experts.