Applied AI Engineer
About Future
Since launching in 2017, Future has grown from a brainstorm in a San Francisco cafe into the nation’s largest provider of personal training sessions. In January 2025, Future announced its merger with Autograph, the company founded by 7x World Champion and entrepreneur Tom Brady. We’re poised for massive growth as we expand our brand, forge new partnerships with some of the world’s most iconic athletes, and harness AI to enhance and scale our coaching experience.
As we continue to grow, we’re investing in cutting-edge technology, deepening our roster of elite coaches, and building new partnerships. If you're passionate about shaping the future of fitness, come join us - we’re just getting started.
About the Role
You'll work at the intersection of AI, product, and engineering — partnering closely with cross-functional teams to identify high-impact opportunities, prototype quickly, and iterate based on data. This isn't a research-only role. You'll own the full lifecycle: experimentation, evaluation, deployment, monitoring, and continuous improvement.
Qualifications
Experience with LangChain/LangGraph or similar agent frameworks.
Hands-on experience with LLMs in production: prompt engineering, tool/function calling, structured output, evaluation.
Comfort with async Python, HTTP APIs, and streaming protocols (SSE, webhooks).
Experience with data validation and schema design (Pydantic, JSON Schema).
Ability to debug across layers: from a broken LLM tool call to a misconfigured Terraform resource.
Clear communication: you'll work directly with product, mobile, and backend engineers.
Nice to Have
Familiarity with AWS (Bedrock, ECR, CloudFront, S3, Cognito) or other cloud agent hosting.
Observability and tracing tools (Langfuse, OpenTelemetry, Datadog).
Exposure to evaluation frameworks: LLM-as-a-judge, automated scoring, dataset management.
Infrastructure-as-code (Terraform, CDK).
Responsibilities
Design evaluation harnesses and quality scoring — we use Langfuse, rubrics to measure safety, effectiveness, and personalization.
Own the full loop: prototype a new agent capability, validate it with evals, deploy it to staging and production, monitor traces, and iterate.
Improve reliability, latency, and cost through prompt caching strategies, token budgets, retry logic, and observability.
Write the tools agents use: API integrations with Pydantic validation, exercise search over local databases, structured workout submission.
Benefits
Health Coverage Comprehensive medical, vision, dental, and disability insurance plus tax savings accounts for all eligible employees.
Retirement 401(k) plan with tax-advantaged savings options.
Remote-First Employment eligible to all employees located anywhere in the continental US. No travel required.
Wellness & Development Monthly health and fitness stipend contributing to overall wellbeing, access to a mental health platform, reimbursement for medical travel, and an annual learning & development stipend.
Flexible Time Off Flexible PTO so you can rest, recharge, and take care of life outside of work.

