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 environments 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-efficient 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