Platform Engineer III

HCL Technologies Limited; United States; On-site; USD 130,000 - 185,000; Full time

Job summary

Sapsf in United States is seeking a senior leader to deploy Generative AI and agentic systems for customers, owning end-to-end implementation from integration to stabilization.

You will collaborate with architects, product, and platform teams to deliver scalable, reliable AI solutions with governance and performance at the core.

Qualifications

• Strong hands-on experience delivering AI deployments in production.
• Experience with OpenAI / Azure OpenAI or similar APIs.

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 engineers, contributing to team capability building.
• Participate in customer discussions, providing technical inputs, trade-offs, and solution recommendations.

Skills

Python

APIs

Microservices

Distributed systems

Cloud platforms

Generative AI

LLMs

Debugging

Communication

OpenAI APIs

RAG architectures

Prompt engineering

Agent frameworks

Vector databases

Data pipelines

Observability

Cost optimization

Tools

LangChain

LangGraph

AutoGen

Azure OpenAI

AWS

GCP

Job description

Requisition ID154779-Posted09/03/2026

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
• Participate in customer discussions, providing technical inputs, trade-offs, and solution recommendations

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
• Effectivecommunication 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 tocost, performance, and reliability optimization for AI systems