Technical Product Manager
Summary
Own the technical roadmap for an eCommerce platform serving automotive dealers and aftermarket sellers, focusing on search relevance, site speed, and platform reliability.
About RevolutionParts
About the Role
What You'll Do
- Own the product roadmap for platform health, search relevance, and site performance/latency, and prioritize it against feature roadmaps
- Partner with engineering on architecture and technical tradeoff decisions, bringing product judgment to complex infrastructure and search initiatives
- In postmortems, help distinguish whether an incident stemmed from a missing or poorly defined non-functional requirement versus an engineering execution issue or a known technical limitation
- Define and track performance and search metrics (page speed, search relevance, uptime, conversion impact) and connect them to business outcomes
- Translate technical constraints and platform debt into clear, business-readable priorities for leadership and stakeholders
- Drive discovery and requirements for search and platform improvements, working with data/analytics to validate impact
- Manage cross-functional dependencies between engineering, data, and other product teams on shared infrastructure
What Success Looks Like
- Measurable improvement in site performance (page load time, Core Web Vitals)
- Improved search conversion and relevance
- Reduced platform incidents and a prioritized, actively executing roadmap for platform debt and reliability
Must-Haves
- 5+ years of PM experience partnering directly with engineering on platform, infrastructure, or search initiatives
- 5+ years of professional engineering experience having worked as a software engineer writing and shipping production code - not solely in an adjacent technical role.
- Demonstrated experience owning a technical roadmap against measurable KPIs (latency, uptime, conversion, etc.)
- Comfort in defining both functional and non-functional requirements for a team whose work, at times, may be heavily backend or hidden away from the UI
- Comfortable pulling and validating your own data without the use of a UI (via REST APIs and database queries)
- Familiarity with observability tools like DataDog
- Experience prioritizing platform/technical debt against feature work
- eCommerce or high-traffic web platform experience is a plus!
Nice-to-Haves
- Experience with search/relevance systems (indexing, ranking, auto-suggest) - ideally with Elasticsearch or a comparable engine
- Exposure to marketplace, multi-seller, or B2B platforms
- Experience navigating cloud cost/performance tradeoffs, particularly on AWS
- Background in automotive, parts, or high-growth eCommerce
- Direct experience with relational databases at scale (e.g. Aurora MySQL/PostgreSQL), container orchestration (e.g. EKS/Kubernetes), and asynchronous messaging systems (e.g. queues, pub/sub)
Ideal Skills
- Web performance fundamentals (Core Web Vitals, caching/CDN strategy)
- Understanding of search/relevance systems and how they drive conversion
- Ability to read architecture diagrams and API specs
- Comfortable reading a pull request or codebase to understand behavior, without needing to write production code day-to-day
- SQL and REST API proficiency for independent data analysis
- Familiarity with observability/monitoring tools for SLAs and performance tracking (e.g. Datadog), ideally in AWS-based environments
- Ability to write technical tickets defining both functional and non-functional requirements and define use cases that may be purely technical in nature
- In incident and postmortem discussions, able to ask technically grounded root-cause questions and determine whether the issue traces to a requirements gap (e.g. unspecified non-functional requirement) or a known technical constraint — always tying findings back to customer impact
- Able to translate fluently in both directions — business needs into technical specs, and technical tradeoffs into business terms non-technical stakeholders can act on
- Comfortable pushing back on engineering with data, not just deferring
- Credible enough with staff/principal-level engineers to ask pointed technical questions and hold your ground, without needing to propose the solution yourself
- Bias toward measurable outcomes over feature output
- Strong cross-functional influence without direct authority
- Calm under ambiguity — platform and infrastructure work often lacks clean requirements
Education
- Using AI tools responsibly to accelerate research, analysis, documentation, and problem-solving
- Exercising strong judgment around data privacy, accuracy, and ethical use
- Continuously learning and adapting as AI capabilities evolve