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Location
Hybrid (Prague, Czech Republic)
Seniority
Senior · 4+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 11, 2026. First seen by Alion on Nov 11, 2026. Apify scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Apify runs a cloud platform for web scraping, data extraction and browser automation used by developers, data teams and AI agent builders. Its store lists more than 74,000 ready-made scrapers and automation tools called Actors, which run as serverless programs with built-in proxies, storage, integrations and an MCP server, and the company maintains the open-source Crawlee library. Founded in 2015 by Jan Curn and Jakub Balada out of the Y Combinator Fellowship, the Prague company reports 84,000 customers and grew from profits before raising 2.8 million euros from J&T Ventures in 2024.
Backed by Reflexcapital

Apify is the largest marketplace of trusted tools for AI that automate work on the web. Thousands of Actors get web data, generate leads, monitor social media, track competitors, and integrate with existing apps and agents. Actors are created by a global community of builders who earn from them, while Apify manages infrastructure, billing, and distribution. Learn more at apify.com.

Join us to help people put the web to work. Apify can find missing children, protect consumers from fake discounts across the EU, and feed data to AI chatbots.

Apify is looking for a Senior Search and Recommendations Engineer to join the Discovery team, which owns how people and agents find the right Actor in Apify Store. The foundations are already in place: recommendations, a categorization system that powers Store filtering, LLM-based offline evals, relevance metrics, and A/B testing. With the catalog growing by more than 20% month over month, we need someone who can keep search and recommendations working for both users and builders as it scales. Discovery is one of the highest-leverage problems at Apify: when users and agents land on the right tool, activation, onboarding, and retention follow.

What you'll be working on:

  • Own Store search relevance end to end: retrieval, ranking, and query understanding. Spot where today's setup falls short and decide what to fix first.

  • Get more out of our Recombee setup: tune scenarios, business rules, and signals so recommendations stay relevant for each user, context, and use case.

  • Sharpen our existing evaluation stack (LLM-based evals, relevance metrics, and A/B tests) so it catches regressions early and gives the team results it can trust.

  • Keep discovery healthy as the catalog continues to grow, refining the signals, ranking, and categorization so they hold up as new Actors arrive.

  • Evolve the Actor category taxonomy and the classification system behind Store filtering so every Actor stays findable by browsing and by search.

  • Make Apify Store work for AI agents as well as people, with retrieval and query understanding that return the right Actor on the first call.

  • Shape technical direction for search and recommendations at Apify, and build the team's expertise in both.

Who we're looking for:

Must-haves:

  • 4+ years of software engineering experience, including 2+ years owning search or recommendation relevance in production at a marketplace, e-commerce, or content platform, ideally one with a fast-growing catalog.

  • Judgment that comes from having done this before: you can look at an existing search, ranking, or recommendation setup and tell where it's headed for trouble, and which problems to leave alone.

  • Hands-on experience in search relevance: ranking functions, query understanding, filtering, and sorting.

  • Experience configuring and tuning recommendation systems, including cold-start and sparse-data problems.

  • Experience evolving category taxonomies and classification for a large, growing catalog, whether by rules, models, or LLMs.

  • Rigor in measuring relevance: you know which metrics and evals to trust, and you've used A/B tests to change product decisions.

  • Strong backend skills for shipping production services and data pipelines in TypeScript/Node.js.

Nice-to-haves:

  • Embeddings, hybrid lexical and vector retrieval, and LLMs applied to retrieval, re-ranking, query rewriting, or evaluation (LLM-as-judge).

  • Enough React/TypeScript to ship changes to Store search and listing pages yourself.

  • Ability to explain ranking trade-offs to product, design, and data colleagues, and to turn "help users find the right tool" into measurable goals.

Our tech stack:

  • Frontend: React.js, styled-components, Storybook, Chromatic, Cypress, Playwright

  • Backend: TypeScript/Node.js, Nest.js, Next.js, Docusaurus, Vitest

  • Infra: AWS Compute (Kubernetes (EKS), EC2, Lambda), Helm, Terraform, CloudFormation, MongoDB, Redis, DynamoDB, S3, GitHub Actions

  • Monitoring: Grafana, Prometheus, OpenTelemetry, Mezmo, Sentry, PagerDuty

  • Tools: GitHub, Notion, Google Workspace, Slack

  • OS, code editor, and AI assistant of your choice (Claude premium with unlimited tokens, GH Copilot, Cursor, Gemini, or JetBrains AI)

  • Process: kanban, code reviews, tests, automating whatever we can, and deploying multiple times per day.

Role-specific tools: Recombee, MongoDB Atlas, and GrowthBook.

What we expect from you in the first 6 months:

By the end of the first 3 months, we expect you to:

  • Audit current Store search, recommendations, and categorization, and present where you see the biggest risks and opportunities.

  • Review our evals and relevance metrics, and close the gaps that would let a bad ranking change slip through.

  • Ship your first relevance or recommendation improvement to production, validated by an A/B test.

  • Ship and debug changes across the discovery stack: Store frontend, scoring and ranking services, Recombee, and the data pipelines behind them.

By the end of the first 6 months, we expect you to:

  • Be the go-to expert for search and recommendations, and set the team’s technical direction.

  • Ship changes that measurably improve a core discovery metric, such as search success, first Actor run, or activation.

  • Deliver a significant upgrade to retrieval, filtering, or ranking, live in production.

  • Ship improvements to the category taxonomy that matches how users and agents search.

  • Improve agent-facing discovery so AI agents find the right Actor more reliably, measured by first-week retention.

Why should you work at Apify?

  • Space, support, and autonomy for personal growth, with a direct impact on our success

  • Full-time position in Prague at our amazing office located in 100Yards

  • Option to work remotely

  • Flexible working hours

  • Nobody counts holidays as long as the work gets done

  • Unlimited Claude for every Apifier. We don't count tokens. Just use them well

  • Stock options and profit sharing

  • Free Apify credits for your friends and family to try the platform

  • Free Multisport card

  • Regular massages in the office, mostly covered by Apify

  • We welcome pets, kids, and bikes at the office

  • Epic team buildings and offsites with biking, canoeing, and other adventures

  • Solid education and training budget, conference tickets, internal "Eat & Learn" sessions, and the possibility to work across teams

  • Generous hardware budget

  • Free lunches every day when working from the office

  • Unlimited supply of & and snacks

  • Free entry to the wonderful Prague Zoo

  • Ping-pong, chess, PS5, foosball league after lunch

For more details about Apify and what it's like to work with us, see our Careers page.

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