Note: The job is a remote job and is open to candidates in USA. Envorso Sports runs a professional sports team's fan-facing business through a platform covering ticketing, websites, mobile apps, and planned commerce, CRM, and marketing automation capabilities. The Agentic AI Engineer will design, build, and operate AI-powered agents and internal agent tooling that transform fan and ticketing data into revenue-generating actions, while shipping full-stack web and mobile experiences for fans and marketers.
Responsibilities
- You'll build the agents that turn a pro sports team's ticketing and fan data into revenue: one that catches a stale cart and proposes a win-back offer, another that hands a marketer a segment they can act on without waiting on an analyst
- Then you'll ship the web and mobile surfaces that put that work in front of fans
- On the product side, you'll design agentic features that act on fan and ticketing data, fan scoring, segmentation, and an offers engine that proposes campaigns instead of reporting on what fans did
- On the engineering side, you'll build and own the internal agent tooling: guardrails on what coding agents can touch, PR-review agents that check against the spec, and automated checks that keep frontend and backend in sync as API contracts change
- You'll set the standard the rest of the team works against
- You'll ship the front-end on web (Next.js) and mobile so your agent work reaches fans and marketers, not just an API
- You'll own the full lifecycle, from design and evaluation through deployment, monitoring, and iteration, with no ML platform team to hand off to
- You'll report into product and work daily with a tech lead and engineering team mostly based in Argentina, so expect overlap-hours collaboration
Skills
- 3+ years of software engineering with at least a year building and shipping AI/LLM-powered applications in production, not a prototype that never left a notebook
- Strong in TypeScript and comfortable in both a Next.js app and an API-service codebase
- You've done multi-agent design, tool use, memory, and orchestration, not a single prompt-and-response wrapper
- You're full-stack enough to ship a feature end to end, including the web UI
- The builders who do well here can explain what an agent is doing, where it breaks, and why, to a product person or a non-ML engineer
- They're comfortable deciding what the right thing to build is rather than waiting for a fully scoped ticket
- You must be authorized to work in the US
- Python is a plus
- Ideally the mobile UI that surfaces it
Benefits
- Bonus and benefits
- Direct exposure to team owners and sports executives
- Minimal process in between
- Hybrid work in Seattle, WA or remote in the US
Company Overview