Job Description
Job Overview: We’re looking for an engineering leader who stays close to the code, holds a high technical bar, and can translate product priorities into shipped software without losing momentum. You’ll manage a team of software engineers, collaborate directly with product management on roadmap execution, and operate as a peer to architecture and platform peers across Exostar’s R&D organization. You will use AI coding tools — Claude Code, GitHub Copilot — yourself, daily. You will model that behavior for your team. AI-native development is not optional at Exostar; it’s how we build. This role reports to the Director, R&D Engineering and operates in Exostar’s FedRAMP Moderate / CMMC Level 2 environment serving defense primes including Boeing and BAE Systems. What You’ll Own Engineering Delivery Lead a team of software engineers building production features across Exostar’s identity, credentialing, and supply chain security platform. Own the technical quality of your team’s output — architecture decisions, PR reviews, code quality, and production reliability. Drive sprint execution: planning, backlog refinement, dependency management, and delivery against committed milestones. Identify and resolve blockers before they become delays — escalate when needed but own the outcome. Establish and maintain engineering metrics: deployment frequency, change failure rate, cycle time, defect escape rate. AI-Native Engineering Leadership Use Claude Code and GitHub Copilot daily in your own workflow — not as optional productivity tools, as standard practice. Model AI-native development for your team: code generation, agentic workflows, AI-assisted PR review, and automated testing. Drive adoption across your team: coach skeptics, celebrate early adopters, measure impact, and share learnings org-wide. Stay current on the AI tooling landscape — surface new tools and workflows to the Director when they’re worth evaluating. Product & Roadmap Collaboration Partner with product managers to translate roadmap priorities into engineering scope — push back on ambiguity, not on accountability. Participate in quarterly planning: capacity estimation, sequencing, and dependency identification across teams. Maintain clear line of sight from customer commitments to sprint execution for your team. Surface engineering constraints to product early — don’t absorb scope silently, negotiate it explicitly. People Leadership Build and sustain a strong engineering team by hiring well, developing talent, addressing performance gaps, and making tough decisions when required. Lead consistent 1:1 conversation that prioritize coaching, development, and long-term impact. Build a team culture of end-to-end ownership: engineers who ship, monitor, and stand behind their systems in production. Partner with the Director on career development frameworks and internal promotion pipelines. Your day if you join us: Essential Job Functions Required: 7+ years of software engineering experience, with 3+ years in an engineering leadership capacity managing a team. Hands-on daily user of AI coding tools — Claude Code, GitHub Copilot, or equivalent. You use these yourself, not just advocate for them. Comfortable in code: you conduct meaningful PR reviews, write production code when it unblocks the team, and can challenge architecture decisions with technical depth. Cloud-native engineering experience on Azure or AWS — microservices, containerization, CI/CD, IaC. Strong written and verbal communication — you can write a crisp engineering spec and hold your own in a cross-functional planning session. U.S. Person. We are not able to consider candidates requiring sponsorship. Location: Hybrid- Herndon, VA, Cincinnati, OH (3x/week) Preferred Qualifications: You are exactly who we are looking for if you: Experience in a FedRAMP, CMMC, HIPAA, or equivalent regulated environment — understanding of how compliance requirements land in the SDLC. Azure depth: Entra ID, managed identities, Azure DevOps, Azure Gov familiarity. Exostar’s primary stack: C#/.NET, Angular, Python, TypeScript, Kubernetes, Terraform. IAM, PKI, credentialing, or federated identity domain experience. Experience building or operating agentic AI workflows: MCP, multi-tool pipelines, AI-assisted code review or testing. Track record of driving AI tooling adoption at team scale — teach-the-trainer models, adoption measurement, coaching skeptics. Why