Manager, Software Engineering

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, Git Hub 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.

• 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 — elevate when needed but own the outcome.
• Establish and maintain engineering metrics: deployment frequency, change failure rate, cycle time, defect escape rate.

• Use Claude Code and Git Hub Copilot daily in your own workflow — not as optional productivity tools, but 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 organization‑wide.
• Stay current on the AI tooling landscape — surface new tools and workflows to the Director when they’re worth evaluating.
• 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.
• 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 prioritise 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.

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, Git Hub 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:

• Experience in a FedRAMP, CMMC, HIPAA, or equivalent regulated environment — understanding of how compliance requirements land in the SDLC.
• Exostar’s primary stack: C#/.NET, Angular, Python, Type Script, 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…