Staff Product Engineer, Developer Experience

Ancestry

2d•$135,000 - $160,000•Hybrid

About The Position

Ancestry is a global leader in family history, connecting people with their past to discover, preserve, and share their unique family stories. The Engineering Productivity team owns how software is made at Ancestry, managing the CI/CD platform and tools like GitHub, Harness, Jira, Confluence, and Figma. They also build internal platforms for cost governance, developer metadata, entity APIs, and CLI tooling with AI agents. Their customers are the engineers, product managers, and designers at Ancestry, and the team's goal is to save them time and improve their output. This role is a product-focused engineering position that ships code, owning a specific part of the developer experience from conception through adoption. The individual will act as the product manager, designer, and engineer for their area, engaging with users, defining problems, designing solutions, building them, and measuring their impact. The work involves building new products from scratch and applying AI, with the flexibility to create automations, polished interfaces, agents, or determine that no new tool is needed. A high standard of quality for internal tools, comparable to customer-facing products, is expected.

Requirements

5+ years of professional software engineering experience, excluding internships.
A track record of shipping software that users chose to use.
Experience leading a complex project from an unclear requirement through launch, coordinating with other teams and making sound scope and implementation tradeoffs.
Proficiency in at least one relevant engineering area, such as TypeScript and React or a backend language like Go, Python, Java, or Rust, with the ability to work effectively across adjacent layers.
Experience building developer-facing software such as CLIs, internal platforms, SDKs, CI/CD tooling, or IDE integrations, and the ability to explain its usefulness.
Ability to seek input from users, reason carefully about interaction and failure states, and communicate clearly in specs, documentation, changelogs, and launch notes.
Ability to reason about where LLM-based capabilities will be helpful, including failure modes and appropriate human review.
Proactive in talking to users and discerning their needs versus their requests.
Strong writing skills for specs, documentation, changelogs, and launch notes.
Comfort with ambiguity and the ability to add structure to it.

Nice To Haves

Experience with Harness, GitHub Actions, Buildkite, or similar CI/CD systems, including release orchestration at scale.
Experience automating against Jira, Confluence, GitHub, or Figma APIs, or building apps within those products.
Experience with agent frameworks, MCP servers, retrieval, or evaluation systems in production.
Experience measuring developer productivity using DORA, SPACE, or DevEx-style methods, with good judgment on how measurements can be misused.
Experience with terminal UI frameworks like Bubble Tea or Textual, design systems, or internal developer portals like Backstage.

Responsibilities

Own a specific developer workflow, tool, or user problem through discovery, definition, design, build, rollout, and adoption, including the decision to keep it, change it, or retire it.
Run own product discovery by interviewing engineers, product managers, and designers, observing their work, and analyzing support tickets, usage data, and CI logs to identify the most critical problems.
Translate learnings into a plan, framing the problem, defining the target audience and their changes, deciding what not to build, and sequencing the smallest useful releases.
Design the user experience, including flows, states, empty states, and error cases, prototyping in Figma or code to reach a real answer faster.
Build the necessary components for the solution, which may include TypeScript and React interfaces, backend services and APIs, CLIs and terminal UIs, GitHub Apps and Actions, Harness pipeline templates, and integrations with Atlassian and Figma.
Utilize AI in owned workflows for agent functionalities, context and tool design, and MCP servers, ensuring dependability through evaluations, human review points, cost and latency budgets, and guardrails.
Maintain a consumer-grade quality bar for internal software, focusing on perceived latency, responsiveness, accessibility (WCAG 2.1 AA), clear error messages, and accurate documentation.
Define the desired outcome upfront to prove the work's impact, instrument adoption, publish findings, and let results guide future actions.
Earn adoption without direct authority by collaborating with design partners, piloting with teams, writing launch announcements, holding office hours, and providing clear migration paths.
Transform one-off successes into reusable building blocks, making technical decisions for owned areas and ensuring resulting patterns are easily adoptable by teammates.