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Product Engineer Manager
GetVocal AI. Own the product roadmap with Product, providing technical context, feasibility, sequencing and engineering trade-offs .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates strong technical ownership of product areas, with expertise in Python, system architecture, and CI/CD practices. Capable of leading engineering teams, improving production reliability, and effectively communicating technical decisions to stakeholders.
Highest-signal resume keywords
Python ProgrammingCI/CD PracticesSystem ArchitectureTechnical LeadershipProduction Software Systems
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Production Code WritingAutomated TestingAPI DesignDatabase ManagementDistributed SystemsTechnical SpecificationsIncident DiagnosisTechnical Trade-offsSystem Reliability DesignScalability Engineering
Soft Skills
Strong CommunicationHigh OwnershipPragmatismTeam CoordinationProduct Judgement
Tools & Technologies
AI Coding ToolsClaude CodeCodexCursorGemini CLI
Industry Keywords
Software DevelopmentProduction EnvironmentsObservability ToolingTechnical Debt ManagementEngineering Standards
Tech Stack
Tools & technologiesDistributed SystemsPython
About the role
Key responsibilities & impact- Own the product roadmap with Product, providing technical context, feasibility, sequencing and engineering trade-offs
- Own features from problem definition through production, including technical specifications, planning, resource allocation, implementation, testing, release and post-release monitoring
- Take technical ownership of the product area, managing architecture, code quality, security, reliability, scalability and technical debt
- Write meaningful amounts of production code
- Build and evolve backend services and product capabilities using Python as a core part of the stack
- Break complex product requirements into clear technical plans for engineers and AI coding agents
- Own the release lifecycle, including CI/CD, release readiness, deployment and rollback strategies
- Improve development velocity and reduce time from agreed idea to production
- Monitor production behaviour and improve uptime, error rates, latency, incident frequency and product reliability
- Lead technical investigations into incidents and turn findings into engineering improvements
- Use AI coding tools for implementation, testing, debugging, refactoring, documentation and technical exploration
- Review AI-generated and human-written code with equal engineering scrutiny
- Coordinate engineers across internal and offshore teams, including hiring, onboarding and technical development where required
- Give Product and Engineering leadership visibility into progress, risks, trade-offs, incidents and delivery commitments
- Raise engineering standards through pragmatic technical leadership
- Deliver quarterly product commitments, improve production reliability, and reduce lead time to production
Requirements
What you’ll need- Strong experience building and operating production software systems
- Excellent software engineering fundamentals and strong hands-on Python experience
- Experience owning significant product functionality from specification through deployment and operation
- Strong understanding of system architecture, APIs, databases, distributed systems and production environments
- Experience designing systems for reliability, scalability, security and maintainability
- Strong understanding of automated testing, CI/CD and modern software delivery practices
- Experience diagnosing production issues using logs, metrics, traces and other observability tooling
- Ability to make sensible technical trade-offs between speed, complexity, quality and long-term maintainability
- Strong product judgement — you understand why something is being built, not only how to build it
- Experience leading other engineers technically without becoming disconnected from the codebase
- Comfortable coordinating multiple engineers or distributed/offshore development teams
- Strong communication skills and the ability to communicate technical decisions, risks and trade-offs clearly to non-engineering stakeholders
- High ownership, pragmatism and comfort operating in a fast-moving environment
- Already using tools such as Claude Code, Codex, Cursor, Gemini CLI or equivalent AI development tools as part of your normal engineering workflow
- Ability to turn product requirements into clear, AI-executable technical tasks
- Ability to use AI agents to explore multiple implementation approaches quickly
- Ability to run multiple development or investigation workflows in parallel where appropriate
- Ability to review and challenge AI-generated code rather than accepting it blindly
- Ability to identify hallucinations, security issues, unnecessary complexity and architectural weaknesses
- Ability to use AI to accelerate test creation, debugging, refactoring and documentation
- Ability to maintain clean architecture and engineering standards while increasing development velocity
- Ability to take full ownership of everything that reaches production
- Capability to design systems independently, understand important technical decisions, and challenge AI tool output
Benefits
Comp & perks- High ownership and autonomy
- Diverse, international team across Europe
- Exposure to cutting-edge AI, voice, and enterprise deployments
- Fast-paced environment with strong learning curve
- 25 days holiday + public holidays
- Private healthcare with 50% coverage for you, and 100% coverage for your kids
- Swile
- Pension contribution
- ESOP/VSOP (shares)