GenAI Python Engineer

Develop end-to-end Generative AI (GenAI) applications with a focus on Retrieval-Augmented Generation (RAG).

• Integrate, parse, and process data from various sources, including documents, images, and structured databases.
• Store and manage extracted content in vector databases, building robust retrieval and evaluation pipelines.
• Ensure high solution quality through defined performance metrics and ground-truth validation.
• Collaborate with cross-functional teams to deliver scalable, secure, and enterprise-grade AI solutions., Design and build GenAI/RAG applications utilizing data from multiple enterprise systems.
• Integrate with structured (databases, APIs) and unstructured (files, document repositories) data sources.
• Develop pipelines for document/image parsing and extraction using OCR and document intelligence tools.
• Structure and process extracted content for downstream AI applications.
• Store parsed data in vector databases and manage embeddings for efficient retrieval.
• Optimize retrieval pipelines (chunking, indexing, metadata tagging, filtering, reranking).
• Build workflows for querying and enriching data from relational and enterprise databases.
• Implement strong evaluation practices (accuracy, relevance, hallucination checks, response quality).
• Work closely with architects, platform teams, and stakeholders to deliver scalable and secure solutions.
• Adhere to enterprise standards for security, governance, observability, and performance.

Strong hands-on AI/ML engineering experience, especially with Generative AI use cases.

• Experience in building RAG applications in enterprise settings.
• Expertise in document parsing, OCR, and image data extraction.
• Familiarity with LLM orchestration frameworks and prompt engineering.
• Experience with vector databases and semantic search.
• Excellent Python programming skills.
• Experience with SQL/NoSQL databases and data integration patterns.
• Understanding of GenAI evaluation frameworks and ground-truth validation.
• Experience in building scalable APIs/services and production AI workflows.

Preferred Skills:

• Experience with Azure AI stack.
• Exposure to high-volume document processing.
• Familiarity with enterprise architecture, security, and compliance.
• Experience with monitoring, model evaluation, and AI observability tools.

Preferred Profile:

• Able to independently build and deploy GenAI solutions from data ingestion to evaluation.
• Strong problem-solving ability and practical implementation approach.
• Comfortable working across data engineering, AI engineering, and system integration.