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

·       Deepen LLMOps capabilities, including prompt versioning, golden datasets, automated evaluations, cost tracking, feedback loops, regression detection, and release controls

·       Own secure integrations with CodeBeamer, GitHub, and event-driven APIs or webhooks

·       Establish operational discipline through logging, alerting, rollback, test coverage, runbooks, rate limiting, and supportability

·       Partner with engineering, IT, security, and compliance stakeholders to support auditable AI-assisted workflows

·       Own and evolve the Platform AI to provide standard and secure approach to access AI assisted capabilities across the organization for certification workflows

·       Mentor and coach other senior/intermediate engineers on team, provide technical guidance, and conduct architectural review for trade offs

·       Help define technical trajectory of the platform and AI tools

Qualifications

·       10+ years of relevant experience

·       Bachelor’s Degree in engineering related discipline preferred

·       Strong Python backend engineering and API integration experience

·       Strong Azure platform experience, especially Container Apps, VNet/private endpoints, Entra ID, Managed Identity, Key Vault, PostgreSQL, ACR, and monitoring

Hands-on experience with LLM application frameworks such as LangChain, LangGraph, or close equivalents

·       Hands-on experience with LLM observability or evaluation tooling such as Langfuse or equivalent tracing and eval systems

·       Experience building CI/CD and infrastructure as code with Terraform, Bicep, GitHub Actions, Azure DevOps, or comparable tools

·       Experience securing internal platforms with RBAC, secrets management, service-to-service auth, webhook validation, rate limiting, and audit logging

·       Ability to design reliable multi-step or agentic workflows, including retries, state handling, guardrails, and output validation

·       Strong operational judgment around testing, rollback, monitoring, alerting, documentation, and runbooks

Strongly preferred

·       Experience in regulated, safety-critical, aerospace, defense, medical, or similarly controlled environments

·       Familiarity with DO-178C-style traceability, auditability, formal review workflows, or human-in-the-loop approval requirements

·       Experience integrating with CodeBeamer, GitHub Enterprise, Jira, or similar enterprise engineering systems

·       Familiarity with C/C++ code analysis or test-generation workflows

·       Experience with prompt governance, change control, and evaluation datasets

·       Some comfort with internal-tool UI work such as React, though this should remain secondary to platform, backend, and infrastructure strength

Sound Exciting? Get in touch today! We have very robust benefits including: 

• Low-cost Medical / Dental / Vision coverage options 
• 401K with generous employer match 
• Responsible Paid Time Off + 11 Paid Holidays 
• Remote work opportunities based on role 
• Employee Assistance Program (EAP) 
• Career growth and professional development opportunities 

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.