Senior LLM Engineer: Enterprise AI Agents & RAG

LTM; Irving (TX); On-site; USD 120,000 - 210,000; Full time

Benefits offered by this job

Comprehensive Medical Plan Covering

Disability Coverage

401(k) Plan with Company match

Life Insurance

Vacation Time, Sick Leave

Paid Holidays

Paid Paternity and Maternity Leave

Job summary

LTIMindtree is seeking an LLM Engineer to design, build, and optimize enterprise-grade AI agents powering store assistant and equipment maintenance solutions. You will focus on LLM integration, prompt engineering, agent orchestration, RAG pipelines, memory management, tool calling, and AI governance to enable reliable, scalable Agentic AI capabilities.

The role collaborates with Product Managers, Data Engineers, Business SMEs, and AI Architects to continually improve agent effectiveness and

Qualifications

• Experience designing enterprise AI agents.
• Knowledge of retrieval augmented generation (RAG) pipelines.
• Experience with tool-calling and agent orchestration.

Responsibilities

• Design and build Agentic AI solutions including orchestrator agents and multiagent workflows.
• Develop RAG pipelines with vector databases and semantic search.
• Create prompts, guardrails, and instructions to improve accuracy and relevance.
• Integrate AI agents with enterprise platforms and services.
• Implement observability and performance monitoring for production AI systems.
• Collaborate with product, data, and AI architects to improve agent effectiveness.

Skills

Prompt engineering

LLM integration

RAG pipelines

Tools

Vector databases

APIs

Job description

LTIMindtree is seeking an LLM Engineer to design, build, and optimize enterprise-grade AI agents powering store assistant and equipment maintenance solutions. You will focus on LLM integration, prompt engineering, agent orchestration, RAG pipelines, memory management, tool calling, and AI governance to enable reliable, scalable Agentic AI capabilities.

The role collaborates with Product Managers, Data Engineers, Business SMEs, and AI Architects to continually improve agent effectiveness and