Future PLC
Applied AI Engineer
Remote role where the employee must remain based in a particular country.
United States only
Employer listed it 4 months ago · Added yesterday
Been open since 4 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
$215k to $250k per year
Location
United States only
Work style
Async
Contract
Full-time
Experience
Mid
Category
Software
Stated by the employer in the job description
Remote flexibility
Work from home
This is a remote role, but the listing expects you to be based in United States.
What the employer says
- Source listing states candidate location: "Remote"
- Listing states: "Remote-First Employment eligible to all employees located anywhere in the continental US."
What Nomaders makes of it
- Confirm with the employer before assuming you can work from another country
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
About Us:
Future is building a personalized guidance system for lifelong health. We help people understand what to do next for their body, goals, and stage of life — then support them in turning those decisions into sustained behavior change. By combining AI, human expertise, personal health data, and accountability, Future helps members improve performance today while building the resilience, capacity, and healthspan they need for decades to come.
About the Role
We're looking for an Applied AI Engineer to help us build and ship AI-powered features that directly improve our product experience and business outcomes. This is a hands-on, product-focused role where you'll take ideas from concept to production — designing intelligent systems, validating them with real users, and turning them into reliable, scalable services.
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.
The ideal candidate is excited about applying LLMs and modern ML tooling to real-world problems. You think in terms of systems, tradeoffs, and outcomes — not just models. You care about performance, quality, latency, and cost in production. Most importantly, you're motivated by shipping impactful AI experiences that customers actually use.
What You'll Do
Build and ship AI agents that serve real users: tool-calling LLM systems with structured output, parallel API orchestration, and streaming responses.
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.
What You Bring
Strong Python skills: you've built and deployed services on large production systems.
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.
Requirements
- ·Strong Python skills: you've built and deployed services on large production systems.
- ·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).
Benefits
- ·We believe great people should be well paid and meaningfully invested in what they're building.
- ·Equity Equity participation offered alongside base compensation.
- ·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.
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at Future PLC, mentioning your remote working experience and working hours (Async).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1d ago. Last checked 23 Sept. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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