Product Engineer
Job Description
At FinQuery, we’ve eliminated the game of telephone between the people who talk to users and the people who write the code. We turned the traditional Product Owner role inside out, moving toward a high-autonomy model where Product Engineers own both the "Why" and the "How." In this role, you aren’t just receiving a backlog of technical specs, you are the strategist, the user researcher, and the builder. You will deeply understand our customers' financial compliance workflows, define the product vision, and then turn around and write the clean, production-grade code to make it a reality. We are looking for a rare hybrid: someone with the sharp product intuition of a veteran Product Manager, backed by the strong technical foundation of a Software Engineer.
Own the Backlog, Shape the Roadmap: Act as product owner for your pod. You will own and groom the backlog for your product area translating roadmap initiatives into clear specs and well scoped stories, sequencing work, and accepting what ships. You will bring user discovery and behavior metrics to roadmap conversations, informing the direction that the Lead Product Engineer sets.
Bridge Business Strategy and Technical Execution: Work at the intersection of business requirements and technical design. You will translate complex domain rules and business logic into clear, actionable specifications and user workflows that engineering teams can build against.
Ship Production Grade Code: Work hands on inside the pod to build, test, and deploy the features you spec. You will collaborate closely with the pod to bring the product vision to life, using your technical grounding to actively participate in design conversations, understand the proposed architecture, and articulate it clearly. By bridging technical details with business goals, you effectively sequence work and communicate key tradeoffs to stakeholders while ensuring solutions are secure, scalable, and auditable.
Amplify Through AI: Use LLM powered development tools, copilots, and automation as a core part of your daily workflow and own what comes out of them. You will move faster with AI while still reading, validating, and standing behind every line it generates, freeing your time for product design and clear requirements rather than outsourcing your judgment.
Own the Outcome: You aren't done when the code is merged. You will monitor releases post-deployment, track feature adoption, gather user feedback, and bring what you learn back into the backlog closing the loop so your solutions actually move the business, not just pass QA.
The Product Mindset: 5+ years in a product-focused role (Product Manager, Product Owner, or Product Engineer) where you routinely owned or contributed to end-to-end feature delivery spec design and definition through release, adoption, and success monitoring.
Architectural Literacy: Ability to understand scalable database schemas, read and review production code with confidence, and understand cloud infrastructure (AWS) implications for the features you scope.
Data-Driven & Empirical: Experience using product analytics tools (e.g., Mixpanel, Pendo, Heap) and SQL queries to validate hypotheses and measure feature success.
High-Bandwidth Communication: Exceptional ability to articulate product decisions and tradeoffs to stakeholders, collaborate closely with UX designers and engineers, and write clear, concise documentation.
Bachelor’s degree in Business Administration, Information Systems, Computer Science, or professional equivalent is required. A strong balance of business acumen and technical literacy is required.
NICE TO HAVES
Prior experience in FinTech, accounting technology, or B2B SaaS platforms.
Experience working in high-autonomy engineering cultures (e.g., continuous deployment, rapid prototyping).
WHAT GREAT LOOKS LIKE HERE
User-Obsessed: You guide product direction and align your pod to solve actual customer pain points, focusing on impactful outcomes rather than just delivery for its own sake.
Highly Autonomous: You don't wait to be handed a fully formed specs, you go write it. You surface ambiguity early, drive it to a decision, and keep your pod unblocked without needing to be managed through it.
Analytically Rigorous: You ground your product decisions in data, user behavior, and strict technical feasibility.
Credible With Engineers: Your pod sees you as a technical peer, not a requirements conduit. You can hold your own in a design review, and you have earned the right to push back on scope because you understand what it costs to build.
