Platform Engineer III

Platform Engineer III

Job Summary

Lead the deployment and solutioning of Generative AI and agentic systems in customer environments by owning end-to-end implementation across integration, testing, and stabilization phases. Collaborate with architects, product, and platform teams to design and deliver scalable, reliable, and production-grade AI solutions, ensuring adherence to standards, governance, and performance expectations.

Key Responsibilities

Lead end-to-end customer deployments across pilot, stabilization, and production phases Design and implement AI solution architectures , including APIs, workflows, integrations, and orchestration layers Build and optimize RAG pipelines, agent workflows, and orchestration frameworks for real-world use cases Define and execute testing, validation, and evaluation frameworks to ensure solution quality and performance Monitor system performance and proactively identify, diagnose, and resolve issues across system layers Work across data, APIs, and platform components to ensure scalable and resilient system integration Drive best practices for safety, governance, and responsible AI implementation across deployments Create reusable solution patterns, accelerators, and documentation to improve delivery efficiency Collaborate with cross-functional teams (engineering, platform, support, product) to align solution design and execution Lead debugging and troubleshooting efforts across production systems, ensuring timely resolution Mentor and guide FDE I, II, and III engineers, contributing to team capability building Skill Requirements Strong expertise in Python and software engineering best practices Deep understanding of APIs, microservices, and distributed system integration Hands-on experience with cloud platforms (Azure / AWS / GCP) and deployment architectures Proven experience working with Generative AI / LLM-based systems in production environments Strong problem-solving and system-level debugging skills Effective communication skills , including ability to engage with customer and internal stakeholders

Other Requirements

Experience with OpenAI / Azure OpenAI or similar APIs Strong knowledge of RAG architectures, prompt engineering, and evaluation frameworks Hands-on experience with agent frameworks (LangChain, LangGraph, AutoGen, etc.) Familiarity with vector databases, data pipelines, and large-scale data handling Experience with observability, monitoring, and performance optimization tools Exposure to cost, performance, and reliability optimization for AI systems