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Salary: USD 180,000 - 300,000 / annual
Sleeper is a fast-growing fantasy sports and real-money gaming platform connecting sports fans through season-long leagues, pick'em contests, and real-time interactions. The company is backed by top Silicon Valley investors including Andreessen Horowitz and General Catalyst.
You will be a Senior or Staff Backend Engineer on the Picks team, building core systems for Sleeper's real-money DFS and prediction markets product. Picks combines two games sharing one wallet: daily fantasy sports (where users pick player stat lines over/under projections) and prediction markets (where users take positions on game and team outcomes at dynamic prices).
Key responsibilities:
- Build and own core Picks systems end to end: contest and entry lifecycle, pricing and market data, settlement and grading, wallet and ledger, eligibility and compliance
- Ensure real-money correctness through reconciliation, auditability, and settlement logic
- Handle real-time systems at scale: continuously moving prices, entry surges before games, settlement across game slates
- Partner with risk and trading teams on exposure management and internal tooling
- Integrate with third-party projection, market, and payments providers, designing for their failures
- Ship features end to end with designers and mobile/web engineers
- At Staff level: own system architecture, raise the bar through design and code review, help other engineers scale
You'll work in a lean, product-driven team where engineers make product decisions, not just implement them. The work directly impacts millions of users and requires deep understanding of production systems at scale.
REQUIREMENTS:
- 5+ years of backend engineering (Staff level: 8+ years with track record of owning system architecture at scale)
- Built and operated consumer products with millions of users; understand code behavior in production at scale
- Shipped features end to end, not only infrastructure
- Experience with systems where correctness costs money: payments, trading, marketplaces, ledgers, or real-money gaming (or equivalent rigor demonstrated elsewhere)
- Deep expertise in distributed systems: data modeling, caching, queues, correctness in real-time updates and concurrent writes
- Strong proficiency in at least one backend language: Elixir, Go, Java, Python, Rust, Node, or similar
- Ability to go deep on your own work: decisions made, what you'd do differently, where your contribution ended and team's began
- Sports fan preferred; experience with DFS, sportsbooks, or prediction markets a plus
- Based in San Francisco Bay Area or New York City, working hybrid
