Platform Engineer III

Job summary

The Platform Engineer III role is responsible for leading the deployment of Generative AI and agentic systems, managing the entire implementation process from integration to stabilization. Key responsibilities include designing AI architectures, optimizing RAG pipelines, and collaborating with cross-functional teams to ensure robust system integration and performance.

Qualifications

• 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

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 to align solution design and execution
• Lead debugging and troubleshooting efforts across production systems, ensuring timely resolution
• Mentor and guide engineers, contributing to team capability building

Skills

Relocation