Key Responsibilities
Design and build LLM-powered applications using proprietary and open-source models.
Implement prompt engineering, Retrieval-Augmented Generation (RAG), tool/function calling, and agent workflows.
Deploy LLM solutions into cloud and enterprise settings with scalability and reliability.
Build inference APIs, microservices, and CI/CD pipelines for AI applications.
Monitor model quality, latency, cost, drift, and hallucinations in production.
Fine-tune and enhance models using parameter-productive techniques where required.
Optimize inference performance using caching, batching, quantization, and prompt optimization.
Ensure security, privacy, and responsible AI guardrails in all deployments.

• Collaborate with product, platform, and engineering teams to deliver enterprise AI solutions.

Required Skills & Experience
Solid programming skills in Python; experience with backend APIs.
Hands-on experience with LLM frameworks (LangChain, Llama Index, or equivalent).
Experience building RAG pipelines using vector databases.
Knowledge of Docker, Kubernetes, cloud platforms, and CI/CD pipelines.

• Familiarity with LLMOps / MLOps tools and monitoring systems.

📌 Walk In Gen Ai Engineer Walk In Interview Chennai
🏢 HCLTech
📍 Chennai