Job highlights

- Proven experience designing and deploying enterprise-scale LLM solutions,multi-agent workflows,and advanced Retrieval-Augmented Generation (RAG) architectures with robust context and memory management systems. Hands-on experience with LLM optimization techniques (prompt engineering,RAG,quantization,distillation,fine-tuning).

- Experience. 5+ Years Required

- 7+ Years Preferred.

Job Summary

AI Platform Lead Engineer The Senior Associate, AI Platform Lead Engineer (Foundation Engineering) will design, build, and optimize the core infrastructure and tooling powering AI agent systems and LLM/SLM applications within the AI Center of Excellence. This individual works at the intersection of AI engineering and backend systems design, building scalable, production-grade foundations for enterprise AI initiatives.

Responsibilities

- Design and develop AI agent frameworks and orchestration layers supporting enterprise use cases

- Apply LLM optimization techniques (quantization, distillation, prompt/context optimization, caching) to improve latency, cost, and performance

- Lead fine-tuning efforts for small language models (SLMs) tailored to domain-specific use cases

- Architect and implement backend services and APIs supporting AI model integration and deployment

- Design and deploy AI infrastructure and services on AWS/cloud platforms

- Implement Model Context Protocol (MCP) integrations to enable standardized tool and data access for AI agents

- Partner with cross-functional stakeholders to translate business requirements into scalable technical solutions

- Mentor Associate-level engineers and review code/design for quality

- Evaluate emerging agentic AI and LLM engineering tools/research and recommend adoption

- Contribute to engineering standards and documentation for the Foundation Engineering practice

Required Qualifications





- Solid proficiency in Python with production-grade backend development experience

- Demonstrated experience with agent development frameworks (e.g., LangChain, LangGraph, AutoGen)

- Proven experience designing and deploying enterprise-scale LLM solutions, multi-agent workflows, and advanced Retrieval-Augmented Generation (RAG) architectures with robust context and memory management systems

- Hands-on experience with LLM optimization techniques (prompt engineering, RAG, quantization, distillation, fine-tuning)

- Practical experience fine-tuning SLMs

- Solid backend development experience including API design, microservices, and system architecture

- Required expertise in AWS and cloud infrastructure (compute, storage, networking, security, deployment/CI-CD)

- Mandatory hands-on experience with Model Context Protocol (MCP) for building standardized agent-to-tool and agent-to-data integrations

- Background in machine learning fundamentals preferred

- Strong communication skills

- Demonstrated stakeholder management skills engaging business leaders, product owners, and cross-functional partners

- Prior experience mentoring junior engineers preferred

Educational Requirements

Bachelors degree required; Masters degree or equivalent postgraduate qualification preferred

Experience

5+ Years Required; 7+ Years Preferred

Physical Requirements

Sedentary Work

Career Level

8IC

Related Skills

- Continuous Integration and Deployment

- Debugging

- DevOps

- Enterprise Application Integration

- Problem Solving

- Programming

- Software Development

- Software Development Life Cycle

- Software Testing

- Systems Design/Analysis

- Systems Development Life Cycle

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Associate - AI Platform Lead Engineer (Mumbai)
🏢 Teachers Insurance and Annuity Association of America (TIAA)
📍 Mumbai