Senior Fullstack Software Engineer, Startpage
Los Angeles, CA, United States1h ago
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Key details
- Salary
- $133K–$183K/yr
- Location
- Los Angeles, CA, United States
- Work style
- Onsite
- Level
- Senior
- Job type
- Full-time
- Experience
- 5–8 yrs
- Function
- Software engineering
- Focus area
- Full stack
- Posted
- 1h ago
Skills
About the role
Startpage is a private search engine with roots going back to Ixquick in 1998, owned by System1 (NYSE: SST) and competing with DuckDuckGo, Brave and Ecosia. We are expanding from search results into a broader set of consumer products for people who want privacy without giving up a modern experience.
You will be a senior full stack engineer on the Startpage Consumer team, a small North America-based group where every engineer works with AI coding agents as a core part of the job. You know how to run agents in loops, coordinate multiple agents on one problem, and judge their output critically. The stack is mostly Python and JavaScript. You will own features from first commit to production across the web frontend, backend services and data pipeline, shape the architecture as the product grows, and pay down the tech debt that slows us. The team ships weekly, so your work reaches millions of monthly users within days.
This position is an onsite role requiring you to work in our headquarters located at 4235 Redwood Ave. Los Angeles, CA 90066.
What you'll work on:
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New consumer products that extend Startpage beyond the search box, on desktop and on the web
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The search results page itself: new features for subscribers and for everyone, within the constraints of our search partnerships
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Real-time decisioning that shapes what a user sees for a given query
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The homepage and engagement features that bring people back
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Traffic quality and abuse prevention for a product that attracts automated traffic
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Data instrumentation and reporting so the team can see what is working
Expect to work across the full breadth of the product rather than one slice of it.
Responsibilities:
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Design, build and ship features end to end, from API and data model through to the UI
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Drive your work with AI coding agents: give them the tools, context and guardrails they need, run them in loops against a spec, orchestrate several agents in parallel on one problem, and review what they produce with a critical eye
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Turn interactive prototypes from product into production code, keeping the intent and cutting what does not hold up
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Own services in production on Kubernetes: deploys, monitoring, the on-call rotation, and the latency and uptime targets a search product demands
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Shape architecture decisions and lead tech-debt reduction so the codebase stays fast to change
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Protect user privacy in every design decision: no tracking, minimal data retention, and no third-party calls that leak queries
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Write automated tests as a matter of course
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Instrument features and read your own results in Sigma and Snowflake; propose the next iteration from the data
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Work with outside partners and agencies so web and app experiences stay consistent
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Write clear tickets, PRs and design notes; review teammates' work the same day
Requirements:
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Daily, hands-on use of agentic coding tools: you can run agents in loops, write the evals that keep them honest, coordinate multi-agent workflows, and know when to take the keyboard back
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5+ years of professional web development, owning both frontend and backend in production
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Strong Python, plus JavaScript or TypeScript, React, and modern CSS and HTML
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Hands-on with Docker, Kubernetes, Helm and Redis
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CI/CD and monitoring tooling, and AWS or a comparable cloud platform; comfortable being paged for what you ship
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Solid automated testing habits
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SQL fluency and the habit of checking your own feature's numbers after launch
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Care for performance: you know what a 100 ms regression costs on a search results page
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Clear written communication with a distributed team and outside vendors
Nice to have:
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Desktop browser or mobile app experience, especially Chromium, Electron or a shipped native app
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Prior search or privacy product experience
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Ads or recommendations systems, especially serving ML models at low latency
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Bot detection, fraud or abuse prevention
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SEO-driven site generation at scale
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Familiarity with EU privacy regulation
How we work:
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Small North America-based team, weekly releases
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Product work starts as a clickable prototype; engineers are expected to push back on it before building
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Agents do the typing; engineers own the architecture, the review and the outcome
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Data over opinion: every feature ships with instrumentation and a success metric
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Jira for tracking, GitHub for code, Sigma and Snowflake for analytics, Slack for the day to day