Job Description: Gen AI Engineer
Objective
Looking for someone with at least 8 years of overall experience, including 6 years in AI/ML and at least 2 years in GenAI.
Role Summary
Seeking a Gen AI Engineer with strong hands-on experience in building end-to-end AI applications. The role requires integrating data from multiple systems, extracting and parsing information from documents and images, interacting with structured databases, storing parsed content in a vector database, and implementing robust retrieval pipelines. The engineer must also ensure solution quality through evaluation frameworks, ground-truth validation, and defined performance metrics.
Key Responsibilities
- Design and build GenAI/RAG-based applications using data from multiple enterprise systems.
- Integrate with structured and unstructured data sources, including databases, APIs, files, and document repositories.
- Develop pipelines to parse and extract data from documents and images using OCR, document intelligence, and related tools.
- Process and structure extracted content for downstream AI use cases.
- Store parsed and chunked content in a vector database and manage embeddings effectively.
- Implement and optimize retrieval pipelines, including chunking, indexing, metadata tagging, filtering, and reranking.
- Build workflows to interact with relational and enterprise databases for querying and enrichment.
- Ensure the application follows strong evaluation practices, including accuracy, groundedness, relevance, hallucination checks, and response quality against ground truth.
- Work closely with architects, platform teams, and business stakeholders to deliver scalable and secure solutions.
- Follow enterprise standards for security, governance, observability, and performance.
Required Skills and Experience
- Strong experience in AI/ML engineering, with hands-on exposure to Generative AI use cases.
- Experience in building RAG applications in enterprise environments.
- Strong knowledge of document parsing, OCR, and image-based data extraction.
- Experience with LLM orchestration frameworks and prompt design.
- Experience with vector databases and semantic search.
- Strong programming skills in Python.
- Experience working with SQL/NoSQL databases and enterprise data integration patterns.
- Understanding of evaluation frameworks for GenAI systems using benchmark datasets and ground-truth-based validation.
- Experience in building scalable APIs/services and production-grade AI workflows.
Preferred Skills
- Experience with Azure-based AI stack.
- Experience with high-volume document processing.
- Familiarity with enterprise architecture, security, and compliance controls.
- Exposure to monitoring, model evaluation, and AI observability tools.
Preferred Profile
- Able to independently build and deploy GenAI applications from ingestion to retrieval and evaluation.
- Strong problem-solving skills with a practical implementation mindset.
