Gen AI Engineer

HCLTech; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

HCLTech Bengaluru is seeking an AI Engineer to design, build, deploy, and operate production-grade LLM solutions for enterprise applications. You will turn LLM capabilities into reliable, scalable systems while improving performance, cost, and user feedback.

Collaborate with product and engineering teams to deliver secure, reusable AI patterns and governance across deployments.

Qualifications

• 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.
• 3+ years of work experience with Python (Programming Language).

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.

Skills

Python

Backend APIs

LLM frameworks

RAG pipelines

Monitoring systems

MLOps concepts

Prompt engineering

Tools

LangChain

LlamaIndex

Vector databases

Docker

Kubernetes

CI/CD pipelines

Cloud platforms

Monitoring tools

Job description

The AI Engineer will design, build, deploy, and operate production‑grade Large Language Model (LLM) solutions. This role focuses on engineering rigor—turning 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.

Experience Level

• 5–10 years of overall software or ML engineering experience.

Success Expectations

• Production‑grade LLM solutions running reliably at scale.
• Continuous improvement in quality, cost‑effectiveness, and user outcomes.
• Reusable AI engineering patterns that accelerate enterprise AI adoption.

Requirements added by the job poster

• 3+ years of work experience with Python (Programming Language)