Platform Engineer III (IN)

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.

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

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

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