Senior Associate - AI Platform Lead Engineer
TIAA (company site, opens in a new tab)5+ yrsPuneOn-siteDirect career pageEst. 20–32 LPA
Posted 20h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and optimize AI agent frameworks, orchestration layers, and backend infrastructure supporting LLM and SLM based enterprise AI applications.
- Lead fine-tuning of small language models and implement optimization techniques like quantization, distillation, and caching to improve latency, cost, and performance.
- Architect and deploy AI infrastructure and backend services on AWS/cloud; implement Model Context Protocol integrations for standardized AI agent-tool/data access; mentor junior engineers.
Minimum Requirements
- Bachelor's degree required; Master's preferred.
- 5+ years of relevant work experience; 7+ years preferred.
- Proficiency in Python with production-grade backend development experience; experience with agent frameworks (e.g., LangChain), enterprise-scale LLM solutions, fine-tuning SLMs, and LLM optimization techniques.
- Mandatory hands-on expertise in AWS/cloud infrastructure and Model Context Protocol (MCP) for AI agent integrations.
Ideal Candidate Profile
- Experienced AI engineer specializing in backend system design and deployment for scalable LLM and multi-agent AI applications within enterprise environments.
- Strong in AWS/cloud platform operations and integration of emerging AI technologies, able to translate business needs into robust technical solutions.
- Capable of mentoring junior engineers and guiding engineering standards in a collaborative, cross-functional setting.