
Full Stack Engineer, Applied AI
Reval · San Francisco Bay Area
- On site
- Full-time
- $250,000 / year
- San Francisco Bay Area
Job highlights
- Build AI intelligence layer for operational execution.
- Productize frontier models into production systems.
- Create agents to dispatch human operator work.
- Develop risk detection and mitigation systems.
- Collaborate on AI engineering patterns and automation.
About the role
Full Stack Engineer, Applied AI
This is a role posted by Reval Recruiting on behalf of a client.
Location:
San Francisco, CA
Workplace:
Hybrid
Employment Type:
Full-time
Visa Sponsorship:
This role offers visa sponsorship.
About the Client:
A fast-growing applied AI and operations technology startup helping companies execute physical work across the U.S. without building local teams, leasing warehouses, or managing every on-the-ground detail directly. Its platform coordinates real-world work across 50+ U.S. metros, covering more than 70% of the U.S. population, and grew from zero to multi-millions in gross revenue in 2025.
Role Overview:
This client is hiring a Full Stack Engineer, Applied AI to help build the intelligence layer behind a platform that turns customer intent into operational execution. This role focuses on productizing frontier models into reliable production systems, including agent loops, retrieval pipelines, internal tools, evals, observability, and full-stack product workflows. This is not an ML research role or foundation model training role; it is a hands-on engineering position building AI systems that reason through operational context, dispatch work to human operators, detect risk, and take action in the real world.
What You'll Do:
- Build full-stack AI product features end to end across React, TypeScript, backend services, database schema, agent logic, and evals.
- Create agents that receive customer requests and dispatch operational work to the right human operators.
- Build systems that proactively surface operational risks and take action to mitigate them before they become customer-facing issues.
- Design agent loops that can plan multi-step actions, call internal tools, ask for help when needed, and recover when reality changes.
- Build retrieval and structured context systems that ground agents in operational data.
- Create evals, monitoring, and production observability to measure agent quality and catch regressions before users do.
- Improve prompts, tool definitions, model choices, and agent architecture based on real production telemetry.
- Partner directly with design and operations to decide what should be automated, what should be assisted, and what should stay human for now.
- Help define shared AI engineering patterns that future products can build on.
Who You Are:
- 2+ years of full-stack engineering experience, with strong product engineering instincts and the ability to own work from UI to backend service to database schema.
- Strong TypeScript experience across frontend and backend, ideally with React, Node, Postgres, and Redis.
- Hands-on experience shipping AI-driven product features in production.
- Working knowledge of LLM APIs, prompting, retrieval, tool use, structured outputs, and evaluation patterns.
- Strong judgment around what should be automated, what should be assisted, and what should remain human-in-the-loop.
- Comfort with messy real-world workflows, noisy inputs, incomplete data, and systems where AI coordinates with human operators.
- Bias toward shipping, learning from production, and iterating quickly.
- Comfort working in an early-stage environment with ambiguity, autonomy, and limited process.
- Interest in building with tools such as OpenAI, Anthropic, custom agent loops, RAG over operational data, in-house evals, Azure, Cursor, Claude Code, and AI-assisted development workflows.
Compensation:
Salary: $200,000 - $250,000 per year
Key skills/competency:
- Full Stack Engineering
- Applied AI
- TypeScript
- React
- Node.js
- Postgres
- Redis
- LLM APIs
- Retrieval Augmented Generation (RAG)
- Production Systems
Skills & topics
- Full Stack Engineer
- Applied AI
- AI Engineer
- TypeScript
- React
- Node.js
- Postgres
- LLM
- RAG
- Production Systems
- San Francisco
- Hybrid
- Full-time
- Visa Sponsorship
How to get hired
- Tailor your resume: Highlight full-stack experience and AI production deployment.
- Showcase AI skills: Emphasize LLM API, RAG, and agent loop expertise.
- Demonstrate adaptability: Prove comfort with early-stage environments and ambiguity.
- Prepare for interviews: Discuss shipping AI features and real-world workflow challenges.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the work arrangement for the Full Stack Engineer, Applied AI role at Reval's client?
- The Full Stack Engineer, Applied AI position at Reval's client is a hybrid role, meaning you will be expected to work from the office some days and remotely on others. Specific details regarding the hybrid schedule will likely be discussed during the interview process.
- Does Reval offer visa sponsorship for the Full Stack Engineer, Applied AI position?
- Yes, this Full Stack Engineer, Applied AI role explicitly offers visa sponsorship, making it accessible to a broader range of international candidates.
- What is the primary focus of the Full Stack Engineer, Applied AI role?
- The primary focus is on building the intelligence layer for a platform that translates customer intent into operational execution. This involves productizing AI models into reliable production systems, not ML research or model training.
- What are the core technologies used by the Full Stack Engineer, Applied AI?
- Key technologies include TypeScript, React, Node.js, Postgres, and Redis. Experience with LLM APIs, prompting, retrieval, and evaluation patterns is also crucial.
- What kind of AI systems will the Full Stack Engineer, Applied AI be building?
- You will build AI systems that reason through operational context, dispatch work to human operators, detect risks, and take action in the real world, including agent loops and retrieval pipelines.
- What experience is required for the Full Stack Engineer, Applied AI position?
- The role requires at least 2 years of full-stack engineering experience, with hands-on experience shipping AI-driven product features in production. Strong TypeScript skills are essential.
- How does this role differ from an ML research position?
- This is a hands-on engineering role focused on *productizing* AI models into production systems. It is distinct from ML research or foundation model training, emphasizing system building and real-world application.
- What is the company's growth trajectory?
- The client is a fast-growing startup that grew from zero to multi-millions in gross revenue in 2025, indicating a rapid expansion and dynamic environment.
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