Top 10 Model tuning react prompting Jobs

Senior Applied AI Engineer
Noon —San Francisco, CA
- $250,000 - $400,000 a year
- Full-time
- Hybrid work
- Office
- 8 years
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Quick Apply
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Senior Applied AI Engineer

Noon -
San Francisco, CA

Quick Apply

Job Details

Full-time
$250,000 - $400,000 a year

Benefits

Stock options
Health insurance

Qualifications

AI models
Software engineering
AI platforms (beyond public GPTs)
Computational framework
Prompt engineering
Production systems
APIs
User flows
Machine learning frameworks
TypeScript
Generative AI

Full Job Description

About Noon

We are on a mission to reinvent how designers work in the AI era. We’re backed by top investors including First Round, Chemistry, Homebrew, Scribble and senior leaders from OpenAI, Meta, Google, Ramp, Stripe and more. We’re building the next-generation AI design tool for product teams.

About the Role

We’re hiring a Senior Applied AI Engineer to ship the AI features that designers actually use every day. You’ll prototype, evaluate, and refine product capabilities — from prompts and agents to retrieval and tool orchestration — and turn raw model capability into reliable, delightful UX. This is a deeply hands-on role for someone who lives at the seam between AI capability and product, can navigate a large TypeScript codebase, and treats fast iteration over polished engineering as a feature, not a bug.

You’ll own AI features end-to-end, capabilities like our AI Cursor, from prompt design and agent orchestration through to the React-aware code transformations that actually ship to users.

What You’ll Do

Build user-facing AI features end-to-end: prompt design, agent flows, tool use, RAG pipelines and the production code that makes them work
Own complex capabilities end-to-end. Take something like AI Cursor from spec to shipped: design the prompt and agent flow, build the retrieval, write the React code transformations, ship the UI, and own the eval
Ship directly into our TypeScript monorepo — your code runs in production, not in a side service
Read and reason about React code as data — the model’s job is to modify React, and yours is to make sure it does so reliably
Iterate quickly on capability vs. UX tradeoffs — when does the canvas need a fast path vs. a slow path, when should the model suggest vs. just execute
Design product-facing evaluation: A/B tests, user-driven metrics, LLM-as-judge harnesses, behavioral regression suites
Own the prompt-engineering, context-engineering, and retrieval layers for every AI feature
Know when a capability has hit the limit of prompting/retrieval and needs fine-tuning or serving-side work - and raise it.
Be the closest engineer to designers and product — translate user intent into AI capability

Must-Have Requirements

8+ years software engineering experience, with demonstrable production AI feature work
Production TypeScript experience in large, complex codebases — you’ve shipped non-trivial features in a TS monorepo and are comfortable owning code end-to-end in a JS/TS stack. This is a hands-on engineering role, not a prompt-tuning role.
Strong prompt engineering, context engineering, and RAG fundamentals
Experience designing agent flows with multi-step tool calling
Hands-on experience with LLM APIs and orchestration frameworks (LangChain, LangGraph, DSPy, Vercel AI SDK, or equivalents)
Ability to design and ship product-facing eval pipelines
Strong product instincts — comfortable holding the pen on UX tradeoffs
Move-fast disposition; comfortable with rapid iteration over polished engineering

Nice to Have

Ability to read and reason about React code — components, hooks, state, JSX as a tree. Our AI modifies React code, so understanding what it’s producing is a major plus
Any background in code-generation AI — Copilot-style completion, agentic code editing (Cursor, Cline, Aider, Devin), AST-aware transformations, code-specific RAG, code evaluation harnesses
Experience with streaming AI UX (token streaming, partial renders, cancellation)
Familiarity with WebSocket-based real-time systems
Background shipping AI inside collaborative or canvas-based products

What You’ll Build

Canvas-side AI capabilities, including AI Cursor and successor capabilities
Multi-step agent flows that take a user goal and execute it end-to-end against a React codebase
Retrieval pipelines over the user’s design system and existing codebase
Real-time, streaming AI experiences in the canvas
The eval harnesses that tell us when a feature is shipping-ready vs. needs more work

Benefits

Salary: $250,000-$400,000 base salary
Equity: Meaningful stock options
Health Insurance: Best-in-class coverage for the employee and their entire family
Location: San Francisco HQ

Quick Apply

Refine Your Search

model tuning react prompting jobs

Senior Applied AI Engineer

Senior AI Engineer (Full-Stack)

Forward Deployed Engineer

Software Engineer, AI Agent

Sr. Infrastructure AI Automation Consultant

Kearney Activate Data and AI Solution Architect

Engineer Lead - Assessments Applications

Engineer Lead – Prep and Driver Applications

Java Full Stack Developer

Senior AI Engineer (FTE)

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