The Role

We’re building a new kind of engineering function at Gametime — one that sits within our CX teams, not beside them. As our first AI Engineer on the Ops team, you’ll be embedded directly within Fan Ops and Marketplace Ops as an AI Accelerator — working side-by-side with our customer experience and marketplace specialists to make AI the default mode for how the team operates. Not an occasional tool. The foundation of how every operator at Gametime executes. Today, our ops teams are already resourceful and fast. Your job is to multiply what they can do. You’ll design and build production-grade agentic workflows that automate the repetitive, the analytical, and the operationally complex — from fan issue triage to seller risk monitoring to marketplace optimization workflows. You’ll teach non-technical teammates how to work with AI tools and build their own automations. And you’ll help establish the playbook for embedding AI capability across the entire Operations org. This is a hands-on, move-fast, build-first role. Your measure of success is the number of workflows you’ve permanently transformed and the degree to which operators in your cohort reach for an AI tool before anything else. If you’re looking to advise and document, this isn’t it. If you want to build things that go into production the same day and see the impact directly in resolution times and fan satisfaction, read on.

What You’ll Do

• Identify and document the highest-leverage workflow transformations across Fan Ops and Marketplace Ops by deeply understanding how your stakeholders work and what slows them down
• Design and build agentic workflows that automate high-value ops tasks — fan issue triage and routing, AI-assisted response drafting, refund and dispute resolution, seller risk scoring, event cancellation handling, SLA monitoring and escalation, and more
• Integrate with external and internal Gametime data systems to build tools that operate at the speed and scale our fan experience demands
• Build tools non-technical teammates can actually use — think clean UIs, Slack-based interfaces, scheduled agents, and knowledge retrieval systems — not just scripts that only you can run
• Coach and partner with each operator through a progressive journey: from awareness, to first win, to regular AI integration, to full workflow transformation, to self-sufficiency
• Recognize patterns across your cohort and systematically scale what works — a tool built for one agent should become reusable for their peers across Fan Ops and Marketplace Ops
• Teach and coach operations teammates on how to work with AI tools, build automations, and think in workflows
• Own the full lifecycle of what you build — from design through production deployment, monitoring, and iteration to impact
• Explore and evaluate new agentic frameworks, LLM capabilities, and AI tooling as the space evolves rapidly
• Help define the model for AI-embedded engineering across Gametime’s broader Operations org

What We’re Looking For

Required

• 4+ years of technical operations or software engineering experience, with at least 1 year building production LLM or agentic systems
• Experience building and deploying tools that non-engineers use in production — not just internal dev tooling
• Ability to work closely with non-technical stakeholders, translate their domain knowledge into technical requirements, and communicate what you’ve built in plain language
• Demonstrated experience coaching or enabling others — formally or informally — with evidence that people you’ve helped actually changed how they work
• Comfort with ambiguity — you’ll often be working from “here’s the problem” not “here’s the spec”
• Preferred
• Experience in customer operations, CX tooling, trust and safety, or marketplace operations contexts
• Background in ticketing, e-commerce, or two-sided marketplace environments
• Familiarity with support tooling platforms
• Familiarity with RAG pipelines, vector databases, and evaluation frameworks —particularly for knowledge retrieval and automated response generation
• Experience with data tools (SQL, dbt, Snowflake) — enough to pull your own context without needing a data analyst for everything
• Prior experience in an embedded or cross-functional engineering role
• Background in consulting, solutions engineering, or other client-facing technical roles where you had to earn trust before transforming how someone works

What Success Looks Like

In 90 days, you’ve shipped production agents that Fan Ops and Marketplace Ops teams use weekly without your involvement. You’ve materially reduced manual resolution time, improved fan satisfaction metrics, and freed up operator capacity. At least multiple teammates can build and modify automations themselves — and they start new tasks by reaching for an AI tool first.

Compensation & Benefits

• Competitive equity package
• Flexible PTO
• Medical, dental, and vision insurance
• Life insurance and disability coverage
• Family-forming benefits via Carrot Fertility
• 401(k) and HSA
• $1,200 annual Gametime event credits
• Company off-sites and wellness programs
• Tenure recognition