Consultant - Gen AI Architect (Senior RAG - Document AI Engineer)

Experience & Skills

• 6–10 years of software engineering experience, including 2+ years building and operating production retrieval and Document AI systems.
• Proven experience building production RAG systems at scale, handling 100K+ documents and millions of chunks, with a strong understanding of retrieval quality, latency and scalability.
• Strong Python development skills, particularly Python 3.11+ and FastAPI, with experience building production-grade APIs and services.
• Hands-on experience with document parsing, OCR and Vision Language Models (VLMs) across PDF, PPTX and DOCX formats.
• Strong understanding of document processing pipelines, including chunking, metadata extraction, embeddings and indexing.
• Experience implementing hybrid retrieval using dense/vector search and BM25, along with rank fusion and reranking strategies.
• Strong understanding of retrieval and RAG evaluation, including Recall@K, nDCG/MRR and groundedness, with experience using evaluation metrics to improve retrieval quality.
• Experience with AWS S3, ECS/EKS, Lambda, Bedrock, Textract and OpenSearch, and familiarity with cloud-native AI architectures.
• Proficiency with Docker, pytest, Git and CI/CD, with strong engineering practices around testing, automation and production reliability.
• Experience in Life Sciences, Healthcare or Pharma is preferred