As an Agentic Engineer at Snapp Stats, you will own the orchestration layer of AI agents designed for sports fans. You will design robust agent loops, manage tool-call latencies, and implement sophisticated evaluation frameworks. This role bridges the gap between experimental LLM hacks and production-ready systems that thrive under real-world user interaction.
Agentic Engineer at Snapp Stats
Snapp Stats is building the ultimate AI conversational companion for sports fans and bettors, backed by a16z and led by the co-founder of Caviar. As an Agentic Engineer, you will move beyond demos to ship production-grade agents that handle long-horizon tasks and real-time sports data. This isn't about weekend hacks; it's about building agents that survive contact with real users. Join an elite, fast-moving team in San Francisco defining the agentic frontier for millions of passionate fans. You will own the orchestration layer, design sophisticated tools, and build the evaluation frameworks that ensure our agents are fast, personal, and accurate.
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Location
San Francisco, United States
Compensation
$160k-$220k + Equity
Company
Snapp Stats
Role overview
Snapp is building AI for the Sports Fan— the ultimate conversational companion for diehard fans to sports bettors.
We use AI agentic systems and LLMs with access to comprehensive sports databases, real-time APIs, and AI-powered content tools to truly engage the passionate fan. Our early adopters are sports bettors and fantasy players looking for detailed insights and personalized recommendations — delivered in an intuitive, easy-to-use experience.
We're venture-backed (a16z speedrun) and led by repeat founders, including the co-founder of Caviar (DoorDash acquisition).
What you will do
- Design and ship complex agent loops that manage long-horizon tasks, tool calls, and partial failures without degradation.
- Build and operate MCP servers to expose rich sports databases and content tools to both internal and partner agents.
- Establish rigorous evaluation harnesses and observability pipelines using tools like Logfire to monitor token spend, latency, and reliability.
Who this is a fit for
- 5+ years of software engineering experience with at least 1.5 years shipping and operating production agentic systems for real users.
- Deep proficiency in production Python, async debugging, and agent frameworks like Google ADK, LangGraph, or Pydantic AI.
- Strong discipline in evaluations and observability, with the ability to move beyond vibes-based prompting to data-driven regression testing.
Why this role is remarkable
- Work at the cutting edge of agentic AI with a16z backing and a leadership team featuring the co-founder of Caviar.
- Direct impact on a product where users notice accuracy and speed immediately, operating at the emotional intersection of sports and betting.
- High-autonomy environment where your architectural decisions and tool designs go from concept to production within the same week.
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