Senior Agentic AI Engineer

Client: TCS | Engagement: Full-time | Work mode: ONSITE | Rate: 60-70 USD | Experience: 8-12 | Publisher job id: 10878617

Role Overview

We are seeking a Senior AI Engineer with deep hands-on experience in designing, developing, and deploying Agentic AI solutions. The role focuses on building autonomous, multi-agent systems that reason, plan, act, and learn across complex enterprise workflows. Key Responsibilities: Design and build Agentic AI systems including planning, reasoning, task execution, memory, and feedback loops. Develop multi-agent architectures including task, reasoning, tool-calling, and orchestration agents. Implement RAG, Knowledge Graph, and Memory-based AI patterns for enterprise use cases. Integrate LLMs with enterprise systems, APIs, tools, and workflows. Define end-to-end AI solution architecture from data ingestion to inference and observability. Build reusable AI services, agent frameworks, and orchestration layers. Ensure scalability, resilience, performance, and security of AI solutions. Define agent evaluation metrics and embed Responsible AI guardrails including governance and compliance. Collaborate with product owners and mentor junior engineers. Required Skills: Strong proficiency in Python. Hands-on experience with Agentic AI frameworks (e.g., LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI). Experience with LLMs (OpenAI, Azure OpenAI, Anthropic, open-source models). Expertise in RAG, embeddings, vector databases (Pinecone, FAISS, Weaviate, Chroma), and prompt engineering. Knowledge of knowledge graphs, ontologies, and semantic search. Cloud experience on Azure, AWS, or GCP. Familiarity with APIs, microservices, and event-driven architectures. Qualifications: 8–12+ years of overall software/AI engineering experience. 3+ years hands-on experience in GenAI and emerging Agentic AI systems. Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field. Preferred Skills: Experience in regulated industries such as pharma, healthcare, or life sciences. Exposure to scientific/R&D workflows or enterprise automation.