Join a leading AI customer experience platform as a senior full-stack engineer. You'll work on integrations, automation, and continuous model improvement, shaping the future of AI-driven customer support for gaming and sports operators. Collaborate with elite engineers, data scientists, and product leaders in a 100% remote U.S. team.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
U.S. Remote | Leading AI Customer Experience Platform
My client is a top provider of AI-powered customer service solutions for the global gaming & sports betting industry, supporting major operators with automation, real-time intelligence, and seamless player support.
They’re expanding their U.S. engineering team to strengthen client integrations and elevate AI performance across the region.
Why Join?
- Shape the future of AI-driven customer support for gaming & sports operators
- Work closely with elite engineers, data scientists, and product leaders
- Blend full-stack development with AI evaluation, model testing, and client delivery
- Competitive pay + performance incentives + possible equity
- 100% remote (U.S.)
The Role:
A hybrid full-stack + applied AI engineering role focused on integrations, automation, and continuous model improvement.
You will:
- Integrate the AI platform with client systems (PAMs, CRMs, ticketing, data APIs)
- Build & maintain custom connectors, SDKs, and automation scripts
- Design and run AI evaluation workflows (accuracy, tone, compliance, latency)
- Support model selection, prompt design, and new environment deployments
- Monitor AI quality via dashboards & internal tooling
- Collaborate directly with Product, AI Engineering, and Client Solutions
Who You Are:
A technically versatile engineer who enjoys working across code, data, and AI behavior, and thrives in fast-paced, high-impact environments.
Requirements:
- 4+ years in full-stack engineering or ML
- Strong with Node.js; experience with Ruby on Rails is a major advantage
- Solid knowledge of APIs, integrations, data flows, and debugging
- Familiarity with LLMs (OpenAI, Anthropic) or conversational AI
- Experience with evaluation frameworks (precision/recall, prompt testing, or human QA)
- Excellent communicator across distributed teams
Bonus
- Experience in gaming, sports betting, or high-volume transactional products
- Knowledge of observability tools (Datadog, Grafana) or experiment tracking
- Interest in AI safety, ethics, and real-world model performance
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