Senior AI & ML Engineer

About Us:

Live experiences help people cross today’s digital divide and focus on what truly connects us – the here, the now, this once-in-a-lifetime moment that’s bringing us together. To fulfill Gametime’s mission of uniting the world through shared experiences, we make it easy for people to discover and access the live experiences that matter most.

With platforms on iOS, Android, mobile web and desktop supporting more than 60,000 events across the US and Canada, we are reimagining the event ticket industry in order to move at the speed of life.

Engineering at Gametime

You will be a key contributor to the Engineering team responsible for building and maintaining the AI and ML platforms that help power the Gametime experience for millions of users. We empower engineers to take full ownership of their code and foster a culture grounded in testing, code reviews, observability, experimentation, and operational excellence. At Gametime, we value collaboration, inclusivity, and the strength of diverse perspectives — creating an environment where people love to build together.

The Role

The Senior AI & ML Engineer is responsible for building and scaling the agentic platform that powers Gametime's conversational experiences and agentic workflows. This person will design, ship, and evaluate LLM-powered features that real customers interact with, touching everything from orchestration and tool use to eval frameworks that keep quality high as the platform evolves. The ideal candidate moves fast without creating tech debt, thrives in ambiguity where goals are clear but implementation is open, and has a track record of putting LLM-powered products into production.

Key Responsibilities:

• Design, build, and ship LLM-powered features and agentic workflows that serve real Gametime users in production.
• Build and maintain evaluation frameworks, prompt testing pipelines, and regression suites that ensure quality and reliability of AI-powered experiences.
• Contribute to the orchestration layer, including agent routing, tool use, state management, and multi-step workflow coordination.
• Develop and optimize prompt optimization strategies, structured outputs, and LLM integration patterns across the platform.
• Propose architecture decisions and technical designs for review by the team's tech lead, balancing speed with long-term maintainability.
• Collaborate cross-functionally with product, engineering, and data teams to translate customer needs into AI system design.
• Stay current with the rapidly evolving LLM and agentic AI landscape, bringing practical new techniques into the team's toolkit.

Key Competencies:

Technical Skills:

• Production LLM Engineering: Proven experience shipping LLM-powered features to real users, including prompt engineering, tool use / function calling, structured outputs, and retrieval patterns.
• Evaluation & Testing: Hands-on experience building eval frameworks, prompt regression suites, LLM-as-judge pipelines, or similar quality infrastructure for AI systems.
• Python Proficiency: Deep fluency in Python as the primary development language, including familiarity with LLM SDKs and multi-agent frameworks such as OpenAI Agents SDK.
• Backend & Infrastructure: Solid backend engineering fundamentals including APIs, state management, data pipelines, and cloud infrastructure.