Principal AI Platform Engineer

Job Title: Principal AI Platform Engineer

Location: Remote - US

Pay Range: $190,000 - $225,000 + Bonus Eligible

Who we are: Lynx delivers modular, open standards–based software that transforms how high-assurance, mission-critical edge systems are built, deployed, and maintained. Our secure edge computing solutions enable innovation and operational excellence in the world’s most demanding environments, from aerospace and defense to commercial and industrial systems. We partner across industries including automotive, medical, and critical infrastructure to deliver tailored solutions aligned with each customer’s mission and operational requirements. Our key products and services are: 

• MOSA.ic: LYNX MOSA.ic™ is a modular software framework and architecture purpose-built for mission-critical edge computing. Based on the Modular Open Systems Approach (MOSA), it provides a flexible foundation for building secure, scalable, and certifiable edge systems.
• LYNX MOSA.ic.AI: LYNX MOSA.ic.AI is a unified CPU and GPU software platform that enables deterministic, certifiable deployment of AI and advanced workloads in mission-critical edge systems. It brings control, performance, and lifecycle governance together, allowing AI to operate predictably within safety-critical environments without compromising certification or system integrity. 
• CoreSuite 2.0: CoreSuite 2.0 is Lynx’s safety-critical GPU for graphics enablement framework designed for mission-critical edge computing systems. It provides hardware-accelerated graphics, visualization, and video processing capabilities that can be certified for high-assurance systems.
• Services: Lynx Services is Lynx’s professional services organization that helps customers design, integrate, certify, deploy, and maintain safety- and security-critical systems. It supports industries like aerospace, defense, automotive, and industrial computing through consulting, engineering, integration, and lifecycle support, reducing development risk and accelerating certification in standards-driven, mission-critical environment.

Role Overview

This should be a builder-architect: someone who can take multiple partially mature AI tools and make them operate like one disciplined platform. The right person should be equally comfortable with engineering architecture, backend integration, cloud infrastructure, LLM tooling, and production hardening.

·       AI workflow orchestration with LangChain / LangGraph or equivalent frameworks

·       LLM observability, prompt/version management, and evaluation systems such as Langfuse

·       Azure platform engineering using Container Apps, PostgreSQL, Key Vault, Entra ID, private networking, and monitoring

·       Secure backend and API integrations with systems such as CodeBeamer, GitHub, and webhook-driven workflows

·       Production hardening through infrastructure as code, CI/CD, testing, rollback, rate limiting, security controls, and auditability

·       Regulated-workflow thinking, where traceability, human-in-the-loop review, and controlled change management matter as much as model quality

Mission for the role

Own the AI platform as the engineering backbone for AI-assisted certification and engineering workflows. This person should make the platform secure, stable, measurable, and extensible so that new AI tools can be built and operated with confidence.

Key responsibilities

·       Define and enforce the platform standard for how AI tools use orchestration frameworks, prompt assets, tracing, and metadata

·       Bring existing advanced tools into alignment with shared platform conventions while preserving important agentic or workflow-specific behavior

·       Build and maintain Azure-based production infrastructure, including networking, identity, secrets, storage, database, monitoring, and deployment patterns

·       Implement infrastructure as code and CI/CD for sandbox-to-production promotion

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