Gen AI /Agentic AI Engineer

HCL Technologies Limited; Dadri, Bengaluru; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

HCL Technologies Limited is seeking a hands-on GenAI engineer to design and build enterprise-grade AI agents that can reason, plan, and act within business workflows. You will collaborate with product managers, architects, and domain experts to define AI solution roadmaps and ensure scalable, secure deployments.

You will integrate LLMs with internal systems, APIs, and databases, fine-tune prompts, and develop production-ready AI services and APIs, driving cost-efficient performance and

Qualifications

• Hands-on experience building GenAI and LLM-powered applications.
• Experience with agentic AI frameworks and multi-agent orchestration.
• Proficient in RAG solutions using enterprise knowledge sources.
• Ability to integrate LLMs with internal systems and APIs.
• Experience designing production-ready AI services and APIs.
• Knowledge of prompting techniques and model performance optimization.

Skills

GenAI development

Agentic AI frameworks

RAG implementations

Enterprise AI integration

Prompts engineering

Security & scaling

Job description

Role & responsibilities

The ideal candidate will have hands-on experience developing applications using Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and enterprise AI platforms. This role involves designing, developing, and deploying intelligent AI agents that can reason, plan, act, and integrate with enterprise systems to automate business processes and enhance user productivity.

Preferred candidate profile

• Design and develop enterprise-grade GenAI and Agentic AI applications.
• Build autonomous and semi-autonomous AI agents capable of reasoning, planning, and executing complex workflows.
• Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources.
• Integrate LLMs with internal systems, APIs, databases, and business applications.
• Create multi-agent orchestration frameworks for complex business use cases.
• Develop copilots, virtual assistants, and AI-powered decision-support systems.
• Fine-tune prompts and optimize model performance, latency, and cost.
• Build secure, scalable, and production-ready AI services and APIs.
• Collaborate with product managers, architects, and domain experts to define AI solution roadmaps.
• Evaluate emerging GenAI technologies and recommend their adoption.