Lead Agentic AI Engineer

Job Description We are seeking a Senior Agentic AI Developer with strong Data Engineering foundations to design, develop, and deploy autonomous AI agent systems for enterprise-scale use cases. The ideal candidate combines deep expertise in agentic AI architectures with hands-on experience in data pipelines, LLMs, and cloud platforms. Role & responsibilities - Architect and develop autonomous AI agents capable of executing complex business workflows with minimal human intervention. - Design and maintain ETL/ELT pipelines that process structured and unstructured data at scale. - Build single-agent and multi-agent systems, incorporating planning, reasoning, memory management, tool/function calling, and workflow orchestration. - Integrate AI agents with enterprise systems, internal APIs, and third-party tools. - Optimize AI applications for performance, scalability, latency, and cost efficiency. - Implement agent evaluation frameworks, observability tooling, and production monitoring. - Apply Prompt Engineering, Prompt Optimization, and Prompt Chaining to improve LLM-driven workflows. - Implement Retrieval-Augmented Generation (RAG) patterns using semantic search, embeddings, and vector databases. - Ensure LLM reliability through guardrails, hallucination mitigation, and AI safety best practices. - Own the full delivery lifecycle: architect, develop, test, deploy, and maintain AI agent solutions from concept to production. - Collaborate with stakeholders across engineering, product, and business teams within Agile delivery frameworks. Agentic AI & LLMs ----------------- - Proven experience designing and building agentic AI systems for enterprise use cases. - Expertise in agentic frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or equivalent. - Hands-on experience building GenAI applications using OpenAI, Anthropic, Google Gemini, or open-source LLMs (Llama, Mistral, etc.). - Strong understanding of LLM concepts including RAG, embeddings, vector databases, and semantic search. - Knowledge of LLM evaluation, guardrails, and AI safety best practices. Data Engineering ---------------- - Strong proficiency in Python and SQL. - Solid experience designing and operating ETL/ELT pipelines for both structured and unstructured data. - Good to have - Hands-on experience with Databricks and/or Snowflake. Infrastructure & Delivery -------------------------- - Experience with cloud platforms: Azure, AWS, or GCP. - Familiarity with Git, CI/CD pipelines, and Agile methodologies. - Strong problem-solving, communication, and stakeholder management skills.