LLM Operations Engineer
Salary not listed • Chennai • Full-time
Posted 2d ago
About the job
We are seeking a skilled AI Engineer specializing in Generative AI and Multi-Agent Systems to design and deploy intelligent, autonomous solutions. This role focuses on building LLM-powered, agent-driven architectures capable of reasoning, collaborating, and executing complex workflows across enterprise systems. You will work on cutting-edge Agentic AI frameworks, enabling systems that go beyond prediction to decision-making, orchestration, and autonomous execution. The position requires utilizing cloud-native services and tools for scalable and efficient deployment, monitoring LLM performance, addressing operational challenges, and ensuring compliance and security standards in AI operations.
Responsibilities
- Design and build multi-agent AI systems for planning, reasoning, and task execution.
- Develop applications using LLMs with advanced prompt engineering and orchestration.
- Implement Agentic workflows including planner, executor, critic, and memory loops.
- Build RAG pipelines with vector databases for enterprise knowledge grounding.
- Develop tool-using agents that integrate with APIs, databases, and enterprise systems.
- Architect and deploy AI copilots and autonomous assistants for business workflows.
- Optimize LLM performance through fine-tuning, prompt chaining, and caching.
- Implement short-term and long-term memory mechanisms using vector stores and knowledge graphs.
- Design multi-agent collaboration protocols.
- Deploy scalable solutions using MLOps & LLMOps practices, including monitoring, evaluation, and guardrails.
- Ensure AI safety, governance, and responsible AI practices.
Requirements
- Minimum 3 years of experience in Generative AI.
- 3–8 years' experience in AI/ML with a strong focus on Generative AI.
- Strong Python development skills.
- Experience building multi-agent orchestration systems with role-based coordination.
- Exposure to agent planning algorithms (ReAct, Plan-and-Execute, Tree of Thought).
- Experience with LLM evaluation frameworks (RAGAS, TruLens, Promptfoo).
- Knowledge of graph-based reasoning and knowledge graphs.
- Experience building autonomous systems or copilots in enterprise environments.
- Systems thinking for designing autonomous AI architectures.
- Ability to balance latency, cost, and accuracy in LLM systems.
- Communication skills to translate workflows into agent pipelines.
- Hands-on experience with LLMs & GenAI frameworks (OpenAI, Hugging Face Transformers).
- Hands-on experience with agent frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel).
- Hands-on experience with RAG pipelines & vector DBs (FAISS, Pinecone, Weaviate).
- Experience building API-driven, tool-integrated AI agents.
- Strong understanding of prompt engineering and optimization.
- Strong understanding of chain-of-thought reasoning and tool augmentation.
- Strong understanding of context management and token optimization.
- Experience with cloud platforms (Azure OpenAI preferred, AWS/GCP acceptable).
- Knowledge of Docker, Kubernetes, CI/CD pipelines.
- 15 years of full-time education.