Gen AI Sr Engineer

We are looking for 8 -10 experienced highly skilled Lead Engineer/Senior Lead Engineer with Experience in designing and optimizing data pipelines for Generative AI solutions integrating LLMs with RAG frameworks using Python vector databases and orchestration tools like LangChain/LangGraph. Well versed with AI Agent Development & Frameworks: Design and scale multi-agent systems using LangGraph/Google ADK to automate complex Root Cause Analysis (RCA) and operational data engineering challenges. Build Human-in-the-Loop agentic workflows that provide actionable recommendations with manual approval gates for critical actions. Develop AI-driven diagnostic tools to correlate job failures and SLA breaches across AWS and Databricks. Collaborate with cross-functional teams (product Engineering and research) to define and deliver AI-powered solutions. Evaluate and select appropriate generative AI architectures and frameworks. Finetune and optimize LLMs for specific use cases and LLM observability to monitor agent performance detect hallucinations and implement iterative updates to prompt chains. Implement AI guardrails and security protocols to prevent prompt injection and ensure the protection of sensitive and maintain AI agent architectures data pipeline integrations and deployment lifecycles. Hands on exposure in LangChain / LangGraph Frameworks for orchestration. RAG (Retrieval-Augmented Generation) implementation Expert level Python with asynchronous programming and data processing libraries (PySpark Pandas). Advanced proficiency in LangGraph/LangChain or Google ADK for building stateful multi-agent understanding of transformer models attention mechanisms and fine-tuning techniques. Hands-on experience with vector databases and advanced retrieval strategies. LLM Observability familiarity with agentic AI evaluation and monitoring tools. Hands-on experience with the AWS ecosystem for -on experience with Databricks Delta Lake and Mosaic with developing and managing workflows using Airflow DAGs. Knowledge of LLM Fine-Tuning (LoRA PEFT). Containerization & Orchestration (Docker Kubernetes). Monitoring & Observability (MLflow Prometheus for AI systems)