Staff Applied AI Engineer

Teamworks is a leading sports tech platform that powers over 6,500 organizations worldwide. They are seeking a Staff AI Engineer to define the architecture and platform capabilities for AI powered product experiences, focusing on building reliable AI systems and providing technical leadership across multiple teams.

Responsibilities:

• Design and define the architecture for production AI systems across the Teamworks platform, including model orchestration services, tool execution layers, evaluation pipelines, and guardrails
• Build reusable backend platform components that allow product teams to integrate AI powered capabilities into their products without rebuilding core infrastructure
• Evaluates and selects appropriate technologies, frameworks, and architectural patterns based on long term scalability, reliability, and team productivity
• Establish engineering standards for building, testing, deploying, and operating AI systems in production, including monitoring, evaluation, and failure handling
• Lead the design and delivery of foundational platform capabilities that enable multiple teams to build and ship AI powered product features
• Design backend services that safely query and operate on multi tenant sports data while enforcing strict data isolation and access controls
• Lead complex cross team engineering initiatives that improve system reliability, reduce infrastructure cost, and accelerate delivery of AI powered capabilities
• Mentors engineers on backend architecture, distributed systems, and GenAI system design

Requirements:

• 8+ years of professional software engineering experience building and operating production systems with significant customer impact
• Proven track record of designing and delivering production AI or machine learning powered product capabilities, including system design, model integration, deployment, and monitoring
• Strong proficiency in TypeScript and Node.js, including building and maintaining backend services and APIs in production environments
• Demonstrated ability to design distributed systems that scale reliably, including clear approaches to service reliability, failure recovery, and performance optimization
• Proven experience designing shared platform infrastructure, internal services, or engineering frameworks used by multiple product teams
• Experience operating cloud based services in AWS, including deployment, monitoring, logging, and incident response for production systems
• Familiarity with analytical data platforms or lakehouse architectures using technologies such as Iceberg, DuckDB, Trino, Spark, or similar query engines
• Background in implementing observability for production systems using tools such as Datadog, OpenTelemetry, or comparable monitoring platforms
• Exposure to Infrastructure as Code practices using tools such as Terraform
• Interest in sports analytics, performance data, or complex domain driven products