Agentic AI Platform Engineer

Agentic AI Platform Engineer

Role:
Agentic AI Platform Engineer

Location:

Denver, CO – Hybrid (2–3 days onsite per week) Duration: 6–12 Month Contract-to-Hire Work Authorization: US Citizen or Green Card Holder Position Overview Client is seeking a hands-on Agentic AI Platform Engineer to help transform AI proofs of concepts into secure, governed, scalable, and production-ready enterprise capabilities. This is an engineering-focused role for someone who can move beyond AI strategy and experimentation and actually build, integrate, test, secure, monitor, and operate AI-powered applications and agentic platforms.

The ideal candidate will have a strong full-stack software engineering background, hands-on experience building AI/agentic applications, and practical knowledge of Microsoft Copilot Studio, Power Platform, APIs, cloud development, identity/security, telemetry, automated testing, and AI tool orchestration. This engineer will work closely with platform and architecture leadership to implement technical controls and reusable capabilities that enable AI agents to operate safely and reliably within a global enterprise environment.

Required Skills:

Hands-on Agentic AI / AI application engineering Full-stack software development background Microsoft Copilot Studio Low-code / Power Platform APIs, integrations and connectors AI agents/tool orchestration Identity/security around AI agents Telemetry/observability Automated testing/evaluation of AI output Cloud development Product ionizing AI POCs SAP and Service Now AI/agent exposure as a plus

Key Responsibilities Design, develop, and product ionize AI applications, AI agents, and agentic workflows. Transform AI proofs of concepts into secure, scalable, reliable, and maintainable production solutions. Build reusable components and platform capabilities for enterprise AI and agentic applications. Develop integrations using REST APIs, SDKs, connectors, webhooks, and enterprise services. Implement AI agent tool orchestration, tool access controls, and integration patterns. Develop and implement sandboxing and isolation mechanisms for AI agents and applications.

Implement secure identity, authentication, authorization, and access-control patterns for AI workloads and agents. Build telemetry, logging, monitoring, tracing, and observability capabilities for AI applications and agents. Develop automated testing and evaluation frameworks to assess AI output quality, reliability, safety, and performance. Implement state management, recovery, error handling, and resilience patterns for agentic workflows. Build and maintain cloud-based AI application components and supporting infrastructure.

Work with Microsoft Copilot Studio and Power Platform to build and integrate enterprise AI capabilities. Develop low-code and pro-code solutions where appropriate, understanding how to integrate both approaches effectively. Establish reusable implementation patterns for AI agents, tools, integrations, and platform services. Collaborate with architecture, security, governance, data, and application teams to ensure solutions meet enterprise standards. Troubleshoot and optimize AI applications across development, testing, and production environments.

Use command-line tools, IDEs, source control, CI/CD pipelines, and cloud development environments as part of day-to-day engineering activities. Help establish engineering standards and technical controls that enable responsible and scalable adoption of enterprise AI.