Ai Ml Engineer

Key Responsibilities

• Design, develop, and deploy GenAI/LLM solutions including prompting, retrieval-augmented generation (RAG), fine-tuning/LoRA, and evaluation.
• Build scalable, secure AWS architectures for AI workloads including API endpoints, model hosting, and data pipelines.
• Implement RAG pipelines: embedding generation, vector stores, retrieval, ranking, and grounding with enterprise data.
• Integrate AI services and custom models with backend applications and databases.
• Write performant PL/SQL for data access, transformations, feature stores, and AI pipeline orchestration.
• Create CI/CD pipelines for model and data workflows; automate infrastructure with Terraform/CloudFormation.
• Establish observability for AI systems (latency, drift, hallucination/guardrails, cost).
• Implement data governance, PII protection, model safety, and access controls.
• Collaborate with product teams and SMEs to define AI use cases (chatbots, summarization, document Q&A, code assist, knowledge search).
• Produce documentation including designs, runbooks, and playbooks; conduct knowledge transfer sessions.