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Future

Personalized coaching with tech-enabled fitness

Applied AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • Strong Python skills and experience building and deploying services on large production systems.
  • Experience with LangChain, LangGraph, or similar agent frameworks.
  • Hands-on experience with large language models in production, including prompt engineering, tool or function calling, structured output, and evaluation.
  • Comfort with asynchronous Python, HTTP application programming interfaces, and streaming protocols such as server-sent events and webhooks.
  • Experience with data validation and schema design using Pydantic and JSON Schema.
  • Ability to debug across system layers, including language-model tool calls and Terraform resources.
  • Clear communication and ability to work directly with product, mobile, and backend engineers.

Responsibilities

  • Build and ship AI agents serving real users, including tool-calling large language model systems with structured output, parallel application programming interface orchestration, and streaming responses.
  • Design evaluation harnesses and quality scoring using Langfuse and rubrics to measure safety, effectiveness, and personalization.
  • Own the full lifecycle of agent capabilities: prototype, validate with evaluations, deploy to staging and production, monitor traces, and iterate.
  • Improve reliability, latency, and cost through prompt caching strategies, token budgets, retry logic, and observability.
  • Build the tools used by agents, including application programming interface integrations with Pydantic validation, exercise search over local databases, and structured workout submission.

Desired Qualifications

  • Familiarity with Amazon Web Services, including Bedrock, Elastic Container Registry, CloudFront, S3, or Cognito, or other cloud agent hosting.
  • Familiarity with observability and tracing tools such as Langfuse, OpenTelemetry, or Datadog.
  • Exposure to evaluation frameworks, including large language model-as-a-judge, automated scoring, and dataset management.
  • Familiarity with infrastructure as code such as Terraform or Cloud Development Kit.

About the Company

Future

Personalized coaching with tech-enabled fitness

Future.co provides personalized online fitness coaching by pairing each member with a world-class coach who designs a customized workout plan and guides nutrition and recovery. The plan is updated over time using progress data from wearables and feedback, delivered through a mobile app with daily coach check-ins. What sets it apart is the combination of ongoing human coaching, data-driven adjustments, daily accountability, and a holistic approach to wellness. Its goal is to make expert personal training accessible anywhere while helping people reach fitness milestones through technology and consistent support.

Company size
501-1,000
Company stage
Series C
Total funding
$113.5M
Headquarters
San Francisco, CA
Founded
2017

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