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JobJob Title: Lead Software Engineer - AI Focused

Department: Product/IT

Reports to: COO

Location: Remote

About Luna Joy

Luna Joy is a leading provider of mental health services, specializing in supporting women through their mental wellness journey. We offer holistic therapy and medication management to help women overcome challenges like postpartum mental health issues. Our dedicated team of professionals works in a collaborative, flexible, and remote environment, ensuring comprehensive care for our clients. We are rapidly expanding and committed to improving access to quality mental health services across the U.S.

Job Overview

We are rebuilding how engineering happens at LunaJoy. Modern AI coding tools, Claude Code, Cursor, and Codex, can now write the majority of production code under human direction. The bottleneck has moved from typing code to scoping problems tightly enough that a fleet of AI agents can execute them without producing pull requests that miss the point. High-impact engineering today isn’t just fast coding; it's about strong systems thinking, sharp specs, and disciplined reviews.

This role is the senior-most engineer at LunaJoy. You will own the technical function - engineering and AI infrastructure. You will set our technical direction, scope work for fleets of AI agents, and own the migration of our codebase to be AI-native and AI-readable end-to-end. Within 3 months, you will be running the engineering function autonomously.

This is not a standard coding role. It is a leadership and orchestration role for someone who has been an engineer their whole career, knows how to ship, and now wants to operate at a higher level of leverage.

Key Responsibilities

  • Lead the architecture, design, and implementation of scalable software systems with embedded AI components.
  • AI infrastructure and agent orchestration. Claude Code workflows, n8n automation flows, agent feedback loops, and the self-improvement infrastructure that makes our agents better over time.
  • The codebase migration to an AI-readable structure. CLAUDE.md hierarchy, file-header docstrings, characterization tests on legacy modules, and strangler-fig migrations of high-risk areas.
  • Specification and review quality. You write the specs that fleets of agents execute against. You are the final review gate for production-bound code.
  • HIPAA-adjacent technical decisions. This role touches PHI. You own the discipline that keeps us compliant and our patients safe.
  • Work closely with data scientists and product managers to translate business needs into technical solutions using ML/AI models.
  • Mentor and guide engineers through code reviews, technical discussions, and career development.
  • Ensure best practices in software development, including testing, monitoring, and documentation.
  • Help manage infrastructure for AI model training, deployment, and monitoring.

Requirements

  • Systems thinking. You hold entire systems in your head, data flows, failure modes, dependencies, where complexity hides, and reason about them as a coherent whole. You catalog information so that AI agents can use it effectively. Without this, every other AI fluency on this list is wasted.

  • Specification precision and phased decomposition. You can take a fuzzy product request and produce a specification tight enough that an AI agent can execute it without supervision, with acceptance criteria expressed as tests rather than English. You can also take a 12-month vision and break it into strategic phases, sub-phases, and individual PRs, each independently shippable.

  • Engineering taste and the bug-sniffing sixth sense. You can look at an AI-produced diff and reliably identify the things that look right but are wrong. This is pattern recognition built up over years of finding bugs in real systems; it cannot be taught quickly, and it is the single most important defense against AI-induced production incidents.

  • Written precision under ambiguity. Most of your day will be spent producing written deliverables, specifications, design docs, PR descriptions, and CLAUDE.md updates. You write clearly when the problem is fuzzy, and you know what to omit.

  • Hypothesis-experiment mindset for AI-product work. You know the difference between deterministic engineering (plan, then execute) and generative engineering (hypothesize, experiment, then commit). When facing an ambiguous AI-product problem, RAG vs. graph, RAG vs. in-context, single-prompt vs. multi-step extraction, your instinct is to set up a small experiment and let the data decide, not to argue from first principles for weeks.

  • Engineering leadership experience. You have led an engineering function or team before. You have owned hiring decisions, made architectural calls, and been accountable for what shipped, not just contributed to it.

  • Pre-GenAI engineering background. You built systems before AI coding tools existed, which is where the systems-thinking and bug-sniffing muscles develop. This is not about age; this is about a specific developmental path that we believe is hard to substitute.

  • AI/agent fluency. You have built with LLMs and AI agents in production. You use Claude Code, Cursor, or equivalent daily. You can articulate the difference between vibe coding and vibe engineering

  • Stack fluency. Strong with Node.js, React, TypeScript. Familiar with AWS or GCP. Comfortable with REST APIs, third-party integrations, and modern CI/CD.

Strongly preferred

  • HIPAA / regulated-industry experience. Healthcare, telehealth, fintech, or another domain where compliance and PHI/PII handling are first-class concerns.

  • Experience as the senior-most engineer at a startup. You are not stepping into an org with peer Staff engineers around you. You will be the technical leader, reporting to a non-engineering CEO.

  • Self-direction and the ability to operate with minimal oversight. Your CEO is not an engineer. You will set direction more than you receive it. Within months, weekly check-ins should be enough.

  • Strong experience in AI/ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
  • Experience deploying ML models in production environments.
  • Solid understanding of system architecture, cloud infrastructure (e.g., AWS, GCP, or Azure), and CI/CD practices.
  • Familiarity with data engineering concepts and tools (e.g., Airflow, Spark, BigQuery, Snowflake).
  • Excellent communication skills and the ability to collaborate with technical and non-technical stakeholders.

Nice to Haves:

  • Prior experience in a healthtech, mental health, or digital wellness company.
  • Exposure to LLMs (Large Language Models), NLP, or generative AI applications.
  • Experience with healthcare or telehealth platforms.
  • Familiarity with HIPAA compliance and data privacy regulations.
  • Experience working in an Agile/Scrum environment.
  • Knowledge of DevOps practices and CI/CD pipelines

Why Luna Joy?

  • Mission-Driven Purpose: Be a part of an organization dedicated to improving access to mental health care, empowering individuals, and creating positive, lasting change in our communities.

  • Remote-First Culture: Designed to support work from anywhere with autonomy.

  • Collaborative & Inclusive Culture: Join a community of diverse talent who share your passion for making a difference. We foster a culture of collaboration, growth, and mutual support to help you thrive in your role.

  • Rewarding Compensation: We recognize the value of your work with fair pay, bonuses, and opportunities for advancement as we continue to expand our reach and impact in the mental health space.

Compensation & Benefits:

  • Compensation Range: $3500+, based on location, experience, qualifications, and applicable federal and state minimum wage requirements.

    • Access to educational resources and professional development opportunities.
    • Supportive community of like-minded professionals.
    • Performance-based bonuses and additional perks.

At Luna Joy, we are committed to fostering a diverse, inclusive, and equitable workplace where all team members feel valued and respected. We believe that diversity of backgrounds, experiences, and perspectives strengthens our ability to support women’s mental health. We encourage individuals from all backgrounds, including those from historically underrepresented groups, to apply and join us in creating a positive impact in our communities. Everyone is welcome at Luna Joy, and we are dedicated to building a work environment where you can thrive and bring your whole self to work

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