Senior Software Engineering Manager
New
S
SimSpaceCybersecurity software
Remote - U.S.Full-TimeManager
SalaryBase salary range: $180,000 - $250,000, with the opportunity for annual bonuses tied to company performance and individual contributions. Equity stock options at hire, with annual performance-based grants.
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Job Details
- Experience
- 10+ years in software engineering, with 6+ years directly managing or leading engineers.
- Required Skills
- KotlinTypeScriptReactCI/CDSoftware Engineering
Requirements
- 10+ years in software engineering.
- 6+ years directly managing or leading engineers.
- Experience leading and growing engineering teams, including distributed or hybrid teams.
- Experience leading teams in spec-driven development with AI, using specs, plans, and acceptance criteria before implementation and verification.
- Experience as a leader adopting AI coding agents and demonstrating how they changed team delivery.
- Experience communicating with cross-org partners about progress, risks, and trade-offs.
- Experience reporting team effectiveness to directors and leadership with clear, candid, evidence-based communication.
- Demonstrated ability to unblock teams, advance engineering maturity, and complete cross-team initiatives.
- Strong technical depth, ideally in TypeScript, React, or Kotlin.
- Preferred: Experience improving end-to-end testing in CI/CD pipelines.
- Preferred: Experience with small batches, short feedback loops, and frequent releases without lowering quality.
- Preferred: Experience owning production services, CI/CD, observability, reliability, and operational ownership.
- Preferred: Bachelor's in Computer Science or a related field, or equivalent practical experience.
Responsibilities
- Lead, grow, and develop a team of engineers, including hiring, onboarding, performance, and career growth.
- Set team direction, goals, and priorities, translating product strategy into a clear plan and predictable execution.
- Establish spec-driven development and AI-native workflows, and set standards for specifying, reviewing, testing, and owning AI-generated work.
- Own end-to-end delivery while balancing scope, quality, and timelines.
- Identify and remove technical, process, and cross-team blockers.
- Lead cross-team initiatives from problem framing and alignment through delivery.
- Improve engineering maturity, including AI-native workflows, spec-driven development, and end-to-end testing in CI/CD.
- Communicate team delivery, quality, and health to directors and leadership with evidence and trends.
- Keep Product, QA, platform, and engineering partners informed of progress, risks, and trade-offs.
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