AI Engineer (LLM / Generative AI/Ops)

HCLTech; Dadri; On-site; INR 1,500,000 - 4,000,000; Full time

Job summary

HCLTech in India seeks an AI Engineer (LLM / Generative AI/Ops) to design, build, deploy and operate production-grade LLM solutions for enterprise applications.

You will implement prompt engineering, RAG, tool calls, and agent workflows; deploy scalable inference APIs and microservices in cloud environments; monitor quality, latency, cost, drift and guardrails, and collaborate with product and platform teams.

Qualifications

• Proficient in Python and backend API development.
• Hands-on with LLM frameworks (LangChain, LlamaIndex, or equivalents).
• Experience building RAG pipelines with vector databases.
• Knowledge of Docker, Kubernetes, cloud platforms, and CI/CD pipelines.
• Familiarity with LLMOps / MLOps tools and monitoring systems.

Responsibilities

• Design and build LLM-powered applications.
• Implement prompt engineering, RAG, tool calls, and agent workflows.
• Deploy LLM solutions in cloud and enterprise environments.
• Build inference APIs, microservices, and CI/CD pipelines.
• Monitor model quality, latency, cost, drift, and hallucinations.
• Collaborate with product, platform, and engineering teams to deliver enterprise AI solutions.

Skills

Python

Backend APIs

LangChain

LlamaIndex

RAG pipelines

Vector databases

Docker

Kubernetes

Cloud platforms

CI/CD

LLMOps

MLOps

Tools

Docker

Kubernetes

Cloud platforms

CI/CD pipelines

LLMOps tools

Job description

AI Engineer (LLM / Generative AI/Ops)

Experience - 5 to 20 years

Role Summary

The AI Engineer will design, build, deploy, and operate production-grade Large Language Model (LLM) solutions. This role focuses on engineering rigorturning LLM capabilities into reliable, scalable, and secure enterprise applications, and continuously improving them based on performance, cost, and user feedback.

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

• Strong programming skills in Python; experience with backend APIs.
• Hands-on experience with LLM frameworks (LangChain, LlamaIndex, 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.