Demonstrates expertise in building and deploying AI agents, with strong proficiency in Python and experience in LLMs, prompt engineering, and API integrations. Capable of collaborating effectively with cross-functional teams while ensuring high-quality evaluation and monitoring of agent performance.

Highest-signal resume keywords

Python ProgrammingLLM ExperienceLangChain/LangGraph FrameworksAPI Integration with PydanticTerraform Debugging

Tech Stack

Tools & technologies

AWSCloudPythonTerraform

About the role

Key responsibilities & impact

Build and ship AI agents serving real users, including tool-calling LLM systems with structured output, parallel API orchestration, and streaming responses
Design evaluation harnesses and quality scoring with Langfuse and rubrics measuring safety, effectiveness, and personalization
Own the full lifecycle from prototyping agent capabilities through evaluation, staging and production deployment, trace monitoring, and iteration
Improve reliability, latency, and cost through prompt caching, token budgets, retry logic, and observability
Build agent tools including API integrations with Pydantic validation, exercise search over local databases, and structured workout submission
Partner with product, mobile, and backend engineers to identify opportunities and iterate based on data

Requirements

What you’ll need

Strong Python skills and experience building and deploying services on large production systems
Experience with LangChain/LangGraph or similar agent frameworks
Hands-on production experience with LLMs, prompt engineering, tool/function calling, structured output, and evaluation
Comfort with async Python, HTTP APIs, and streaming protocols including SSE and webhooks
Experience with data validation and schema design using Pydantic and JSON Schema
Ability to debug across application and infrastructure layers, including Terraform resources
Clear communication and ability to work directly with product, mobile, and backend engineers
Nice to have: familiarity with AWS, including Bedrock, ECR, CloudFront, S3, and Cognito, or other cloud agent hosting
Nice to have: observability and tracing tools such as Langfuse, OpenTelemetry, and Datadog
Nice to have: exposure to evaluation frameworks including LLM-as-a-judge, automated scoring, and dataset management
Nice to have: infrastructure-as-code with Terraform or CDK

Benefits

Comp & perks

Equity participation offered alongside base compensation
Comprehensive medical, vision, dental, and disability insurance
Tax savings accounts for eligible employees
401(k) plan with tax-advantaged savings options
Remote-first employment for employees located anywhere in the continental US
No travel required
Monthly health and fitness stipend
Access to a mental health platform and therapy support
Reimbursement for medical travel
Annual learning and development stipend/budget for courses, conferences, coaching, and tools
Flexible PTO
Free Future platform membership
Meaningful equity package

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonPrompt EngineeringData ValidationSchema DesignAPI DevelopmentAsync ProgrammingStreaming ProtocolsDebuggingQuality ScoringCost Optimization

Soft Skills

Clear CommunicationCollaboration

Tools & Technologies

LangfuseOpenTelemetryDatadogAWSTerraformCDK

Industry Keywords

AI AgentsTool-Calling LLM SystemsEvaluation FrameworksInfrastructure-as-CodeObservability