Artificial Intelligence Engineer

Job Description: GenAI Python Engineer Role Summary Seeking a GenAI 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. • Very 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. • Comfortable working across data engineering, AI engineering, and application integration.