Lead Software Architect — AI Platform Engineering

General Dynamics Mission Systems, Inc•,

3d•$200,723 - $222,678•Hybrid

About The Position

The Lead Software Architect will define the technical vision for the AI platform, including its service boundaries, data flows, integration contracts, and deployment topology. This role involves hands-on architecture work, utilizing working code and operational feedback. The architect will select, evaluate, and replace tools, frameworks, and services, owning the technical direction and defending it with evidence. Responsibilities include writing, reviewing, and debugging production code, setting engineering standards for the platform team (CI/CD, testing, observability, automation, documentation), and owning the operational health of the platform (SLOs, incident response, capacity planning, self-healing automation). The role requires translating architectural intent into shipped capability, defining milestones, managing technical risk, and ensuring predictable delivery of working software. The architect will also work across organizational boundaries with infrastructure, security, cloud, data, and ML pipeline teams, building credibility through personal experience.

Requirements

Bachelor's degree in Engineering, plus a minimum of 10 years of relevant experience; or Master's degree in Engineering, plus a minimum of 8 years of relevant experience.
10+ years of software engineering experience, with at least 4 years in a technical leadership or architecture role.
Personally architected and shipped production platforms.
Deep experience with cloud-native architectures (AWS, Azure, or GCP), including container orchestration, API gateway design, event-driven systems, and infrastructure as code.
Extensive production AI/ML systems experience — model serving, LLM integration, prompt management, or AI pipeline orchestration.
Demonstrated technical depth across multiple domains — application code, infrastructure, networking, data engineering, ML pipelines, security, or platform tooling.

Nice To Haves

Career built at commercial tech companies (product engineering, SaaS platforms, cloud infrastructure, or startups).
Experience with LLM application development — RAG pipelines, embedding strategies, fine-tuning workflows, or multi-model orchestration.
Familiarity with AI-assisted development tools and practices (Copilot, Cursor, Claude Code, or similar) and a perspective on their integration into professional engineering workflows.
Experience operating in multi-cloud or hybrid-cloud environments with complex networking and security requirements.
Track record of mentoring senior engineers and building high-performing platform teams.
Has never worked in defense or government.

Responsibilities

Define the platform architecture, including service boundaries, data flows, integration contracts, and deployment topology.
Select, evaluate, and replace tools, frameworks, and services for the team.
Write, review, and debug production code.
Set engineering standards for the platform team, including CI/CD practices, testing expectations, observability requirements, operational toil automation, and documentation norms.
Own the operational health of the platform, including SLOs, incident response, capacity planning, and automation for self-healing systems.
Translate architectural intent into shipped capability, defining milestones, managing technical risk, and ensuring predictable delivery of working software.
Work directly with infrastructure, security, cloud, data, and ML pipeline teams to ensure technical decisions are implemented across organizational boundaries.