Sr. Engineering Manager (AI-Native)
New
F
Finite StateProduct Security
United States or CanadaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 5+ years of software engineering experience 3+ years of engineering management experience
- Required Skills
- AWSDockerNode.jsPostgreSQLPythonJavascriptKubernetesTypeScriptRedisNext.jsReactCI/CDGitHub
Requirements
- 5+ years of software engineering experience
- 3+ years of engineering management experience leading teams of 5–15+ engineers
- Proven track record of delivering high-quality, production-grade systems with measurable outcomes
- Experience defining and enforcing quality standards through automation and systems
- Experience partnering with Product Management to deliver customer-focused solutions
- Hands-on experience with AI-powered developer tools and workflows (e.g., Cursor, Claude, Codex, or similar)
- Strong understanding of how to apply LLMs and agent-based systems to code generation, testing and validation, and developer productivity
- Ability to evaluate emerging AI technologies pragmatically and integrate them into real-world systems
- Deep understanding of modern testing strategies and quality engineering
- Experience building or scaling automated testing frameworks, CI/CD pipelines with enforced quality gates, and observability systems (metrics, logging, tracing, alerting)
- Experience defining and operating against SLOs/SLIs, reliability and performance targets, and data-driven engineering metrics
- Strong bias toward automation, instrumentation, and continuous validation
- Strong coaching and mentoring skills
- Ability to drive alignment and influence across teams
- Clear communicator across technical and business contexts
Responsibilities
- Lead, mentor, and grow a team (or teams) of 5–15+ engineers
- Drive delivery of software that meets strict, measurable standards for quality, reliability, and maintainability
- Establish clear expectations where quality is owned by the team and enforced through systems, not heroics
- Foster a culture of accountability, continuous improvement, and engineering excellence
- Ensure engineering decisions are grounded in customer outcomes and product impact
- Partner closely with Product Management to translate customer needs into scalable, high-quality systems
- Define and implement AI-driven quality strategies across your teams
- Build and operationalize automated and autonomous testing systems, including AI-generated test cases, self-healing test suites, and agent-assisted validation
- Leverage LLMs and agent-based systems to continuously expand test coverage, identify edge cases, and reduce manual QA effort while increasing confidence
- Design and enforce engineering processes where quality gates are automated and non-bypassable
- Implement AI-powered tooling across the SDLC: code generation and review assistants, automated code quality and security analysis, and intelligent CI/CD pipelines with adaptive testing
- Establish comprehensive observability including logging, metrics, tracing, alerting, and SLOs/SLIs aligned with customer expectations
- Define and implement AI-first development workflows across your teams
- Contribute to and execute the technical roadmap in alignment with business objectives
- Manage technical debt strategically to ensure sustainable velocity and system health
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