AI Engineer – DTC Platform Engineering
PUMA SE (company site, opens in a new tab)4+ yrsPuneOn-siteDirect career pageEst. 18–30 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Build and operate production-grade LLM applications, multi-step agents, and stateful memory systems for product engineering teams.
- Own AI platform capabilities including RAG and retrieval pipelines, model gateways, deployment and monitoring, cloud cost and access controls, and automated evaluation/CI testing.
- Turn AI prototypes into secure, scalable services integrated with enterprise data, codebases, and APIs.
Minimum Requirements
- Work Experience Required: 4+ years in software development, including 2+ years focused on building, testing, and shipping agentic workflows, memory systems, and LLM features to production.
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
- Production experience with stateful AI systems or complex tool-calling agents; agent design patterns, state machines or LangGraph, and stateful memory management.
- Strong Python and/or TypeScript, plus experience with vector stores and embeddings, APIs, Docker, Kubernetes, and AWS, GCP, or Azure; evaluation-harness experience and AI gateway configuration are also specified.
Ideal Candidate Profile
- Has moved agentic and LLM systems beyond prototypes into reliable production deployments, including state, tool integrations, and operational monitoring.
- Brings platform-engineering experience: designing reusable AI gateways and integrations, deployment patterns, evaluation systems, and cloud cost and security controls.
- Can work across product engineering, SRE, and security stakeholders to deliver end-to-end AI capabilities for engineering teams.