Medical Coding Using Ai Jobs in California (NOW HIRING)

About Moon
An ambitious and independent stealth SaaS company incubated by Home Organizers, a market leader with decades of proven success in designing and delivering exceptional, innovative home organization solutions through its subsidiaries Closet World, Closets by Design, Brio Water Technology, and others. Backed by their deep industry experience and a commitment to be Home Organizer's critical SaaS provider for its 6000+ employees, our team is building innovative solutions to solve universal problems that most businesses face - yet are not addressed by a single, unified tool.
Our mission is to transform the entrepreneurial experience and deliver operational excellence for businesses across the world through a unified platform supercharged with proprietary AI agents. We want to unleash the creativity of billions and inspire the world to dream big and build fast. We're a rapidly growing team of forward-thinking and, most importantly, committed builders. We are driven by the opportunity to push boundaries, reimagine the foundations of human work, and shape tools that power the next generation of "business operations." The way the world views and does business is changing, and we are committed to leading this change responsibly.
Role Overview
This is not just a hands-on coder role - it is a force multiplier. You will ship product features while
also being the person who has the opportunity to fundamentally change how the entire
engineering team works. You will own, extend, and continuously evolve the company's proprietary
AI toolkit while leading a company-wide SDLC rebuild powered by AI agents. You will mentor a
distributed offshore team of senior software engineers on using AI tools, design the AI
infrastructure environment for the entire engineering organization, and build AI-powered features
directly into the home services SaaS product. The right person for this role has actually changed
how a team works before - not just used AI tools themselves. The stated goal: 10x engineering
productivity.
About the role
You will pair closely with our engineers, who are already AI-native, and together you become
the AI center of gravity on the team. The offshore team is made up of strong, experienced
software engineers who need mentoring to using AI to its full potential - you are the person
who changes that. You also own the toolkit infrastructure that makes AI work reliably across
the whole organization: the agents, the skills, the context pipelines, and the MCP integrations.
Your impact is measured not just by what you ship, but by how much faster everyone else ships
because of you - and by whether the AI toolkit itself is getting smarter over time.
What you'll do
Moon AI Toolkit - Ownership & Evolution
Own, maintain, and continuously evolve the company's Moon AI Toolkit
Build new agents from scratch - define agent scope, system prompts, tool access, and
evaluation criteria
Write new skills (e.g. Claude Code native skills) that are automatically discovered and invoked
across the engineering workflow
Design new multi-agent workflows that orchestrate specialists in parallel and sequentially to
complete complex engineering tasks
Maintain and improve the agent routing system - ensuring the right agent is dispatched for
every task type, with clear escalation paths
Evaluate agent performance continuously - identify failure modes, rewrite underperforming
agents, and log learnings to the shared knowledge base
SDLC Rebuild with AI Agents
Lead the redesign of the company's SDLC using AI skills and agents as the primary mechanism
of change
Automate or AI-augment every repeatable SDLC step: ticket refinement, code review, test
generation, documentation, and deployment verification
Work directly with the engineering team to roll out changes company-wide - including
training, change management, and feedback loops
Define the measurable productivity baseline and track progress against the stated 10x
improvement goal
Own the rollout roadmap: from POC phase (first 90 days) through team-wide adoption
Full-Stack Feature Delivery
Work across the .NET / C# backend (ASP.NET, EF Core), Python, TypeScript / Capacitor frontend
(cross-platform mobile), and AI integration layer (LLM APIs, RAG, agent pipelines)
Build AI-powered features into the product directly - home services use cases including
scheduling intelligence, recommendations, and workflow automation
Maintain production quality throughout: tests, documentation, and code review for every
feature shipped
AI Environment for the Engineering Organization
Design and implement the infrastructure and tooling environment that makes successful AI
usage possible across all engineers
Own MCP (Model Context Protocol) server configuration and management - the integration
layer connecting AI agents to internal systems (Jira, Confluence, GitHub, Slack, Notion)
Standardize IDE plugin configuration and AI assistant settings across the team
Design and maintain context injection pipelines - ensuring AI agents have access to accurate,
up-to-date project context at all times
Own the onboarding program for new engineers joining the AI-assisted workflow
Context Building & Knowledge Management
Implement engineering org-wide context layer best practices: structured context files
(.claude/docs/ - project-map, known-issues, conventions, decisions, lessons), shared
knowledge management, and AI tool configuration standards
Own the prompt library governance process - curate, version-control, and share high-value
prompts across the team
Establish standards for how agents consume context: what goes in knowledge files, how to
structure agent instructions, and how to keep context current as the codebase evolves
Team Enablement & AI Adoption
Mentor and upskill engineers on AI tooling
Define and roll out AI-assisted development standards across the whole engineering team (e.g.
Cursor, Copilot, or equivalent)
Establish code quality standards and review practices that scale with AI-assisted development
Help translate poorly defined or ambiguous tickets into clear, executable engineering tasks
before work begins
Qualifications
Demonstrated experience driving AI tooling adoption across an engineering team - with
measurable outcomes, not just personal usage
Deep proficiency with AI-assisted coding tools like Cursor, GitHub Copilot, Claude Code, etc. -
you use these daily, not occasionally
Experience building and evolving AI agent systems: agent definitions, multi-agent orchestration,
routing logic, and failure mode analysis
Enough .NET / C# fluency to be credible and effective with a senior engineering team - you
can review their code and spot issues
TypeScript / Capacitor for frontend and cross-platform mobile work - you own the full stack
for AI-powered features
Experience integrating LLM APIs into production applications (OpenAI, Anthropic / Claude,
Azure OpenAI, or similar)
Understanding of Model Context Protocol (MCP) - configuring servers, managing tool access,
and troubleshooting integration issues
Strong code review skills and the ability to set engineering standards that others follow
Comfortable working with ambiguity - you can take a vague requirement and turn it into a
well-scoped engineering task
Nice to have
Experience with RAG (Retrieval-Augmented Generation) patterns or advanced AI agent
workflow design
Background in home services, field service management, or similar SaaS verticals
Experienced with prompt engineering and AI workflow design beyond code generation
Prior experience building Claude Code agents, skills, or custom workflows
The pay range for this role is:
130,000 - 160,000 USD per year (Moon HQ)