2-8 years of software engineering experience in user-facing or backend products.
Experience deploying LLM services in production, including prompt design and orchestration.
Proficient in Python and TypeScript/React, with knowledge of AWS or GCP.
Familiar with RAG, vector databases, embeddings, and retrieval pipelines.
Skilled in building automated tests and monitoring for production AI systems.
Knowledge of agent or workflow frameworks like LangGraph or CrewAI.
Experience with multi-tenant systems in regulated domains like healthcare or fintech.
Responsibilities
Design and maintain agentic systems for complex workflows in various regulated domains.
Build production retrieval-augmented generation pipelines and infrastructure.
Implement multi-agent orchestration and reasoning components.
Develop tools to evaluate model performance and ensure reliability.
Deliver full-stack AI features from APIs to frontend and backend implementation.
Collaborate with product and design teams to prioritize features and improve based on user feedback.
Benefits
Comprehensive health insurance coverage.
Flexible work hours and remote work options.
Professional development opportunities and training.
Generous paid time off and holiday schedule.
Collaborative and innovative work environment.
Full Job Description
About the Role
Join a core product team building agentic systems that automate complex workflows across regulated and enterprise domains. You will ship production LLM-based services and help make them reliable, safe, and useful for customers. What You'll Do
Design and maintain agentic systems for multi-step workflows across areas such as healthcare, legal, fintech, logistics, and compliance.
Build production retrieval-augmented generation pipelines and retrieval infrastructure, including vector databases, embeddings, and indexing.
Implement multi-agent orchestration, tool calling, memory, and reasoning components.
Develop evaluation and safety tools to measure model performance, detect regressions, and support reliable production use.
Deliver full-stack AI features, from APIs and data models through frontend and backend implementation, testing, deployment, and monitoring.
Work with product and design partners to set priorities and success metrics, then improve features using user feedback and telemetry.
What We're Looking For
Two to eight years of software engineering experience delivering user-facing or backend products, including production engineering experience in a product-focused environment.
Practical experience deploying LLM services in production, including prompt design, orchestration, and tool integration.
Proficiency with Python and TypeScript/React or equivalent, plus cloud platforms such as AWS or GCP and relational or NoSQL databases.
Working knowledge of RAG, vector databases, embeddings, and retrieval pipelines.
Experience building automated tests, evaluations, and monitoring for production AI systems, as well as API-driven, high-throughput systems and real-time features.
Familiarity with agent or workflow frameworks such as LangGraph or CrewAI, and orchestration tools such as Temporal or Trigger.
Experience with multi-tenant or enterprise systems, or regulated domains such as healthcare, fintech, or legal; familiarity with fine-tuning or multimodal models is also useful.
A completed university degree and a track record of owning features from data model through deployment and monitoring.
Compensation & Benefits
Base salary: $150,000 to $180,000 annually. Visa sponsorship is not available. Location
On-site in San Francisco, California, United States.
