The company is not a meal kit company. The company is building the most advanced personalized nutrition platform in the world, delivering 16,000+ chef-crafted meals per week, each weighed to the gram, tailored to individual biomarkers and lifestyles, and shipped nationwide in reusable glass jars and bentos.

The company never uses gluten, refined sugar, or canola oil. Meals are designed to produce measurable health outcomes : greater strength, better focus, more energy, better sleep, clearer skin, and sustainable weight management.

- $26M in revenue

- Seed-funded only

- Profitable

- Growing 25%+ year-over-year

- 40 team members at HQ (Concord, California kitchen, warehouse, fulfillment)

- 15 global team members

- Operating with the ambition of a company 10x its current size

What Makes This Role Different :

The company has :

- 9,000+ refined recipes

- 79,861 meal components

- 106,000 component ingredients

- 20,000+ individual ingredients

- 12 million behavioral data points

A backend scoring system with 54 weighted variables blending culinary science, nutritional targeting, operational constraints, and customer personalization

The COO and Head of HQ Ops built an AI Menu Builder prototype in a single overnight session using Claude and React. It takes 54 weighted variables (taste, cost, seasonality, labor, nutrition, inventory levels) and generates optimized weekly menus from 9,000+ recipes.

You are not starting from a blank whiteboard. You are inheriting working prototypes built by operators who deeply understand the domain. Your role is to connect them to the production database and make them real.

Role Overview :

Title : Senior Full Stack Engineer / AI Tech Lead

Compensation : Commensurate with experience and location

Location : Remote (Worldwide).

Reports To : Co-founders (CEO and COO)

Works Daily With :

- Head of HQ Ops (data infrastructure, prototyping)

- CEO/CMO (product vision, marketing, tech)

- COO (physical product design, culinary, operations, finance)

Strategy : Build in Parallel, Not on Top of Legacy :

This role is not about fixing an existing codebase. It is about building a new system alongside it.

The company consulted multiple technical advisors, including founders who have built and exited companies and engineering leaders at companies like Slack.

The consensus :

- Do not fix the legacy codebase through the existing agency.

- Build a parallel system that ingests existing data and runs independently.

- Use the current system as a data source.

- Build modern, AI-first infrastructure.

- Run experiments and prove value without being constrained by old code.

- Migrate users once validated.

This approach enables speed, modern tooling, and measurable progress in weeks rather than months.

What You Inherit :

- Production Database : PostgreSQL on Heroku/AWS with 9,000+ recipes, 79,861 meal components, 106,000 component ingredients, 20,000+ ingredients, 12M behavioral data points.

- AI Menu Builder Prototype : Built in Claude + React. 54 weighted variables. Functional prototype requiring production infrastructure.

- Personalized Nutrition Onramp Prototype : Built in Claude Code, connected to Supabase and Netlify. React/JSX frontend. GitHub repo exists. Requires branding, production DB connection, and polish.

- Backend Scoring System : 54 variables in config file driving menu logic. Needs to become a production service.

Current Stack : Ruby on Rails backend, React/TypeScript frontend, PostgreSQL, Heroku.

Your responsibility :

- Productionize it

- Connect to live inventory and pricing data

- Make it the primary COO tool

- Eliminate 30+ hours of executive time per week

Personalized Nutrition Engine :

- Ingest biomarker data (blood work, health app syncs, lifestyle questionnaires)

- Map health profiles to meal combinations

- Build production pipeline from data input to weekly delivery

The backend scoring logic and React prototype already exist. Advisors believe an MVP can launch in 23 months with the right builder.

Inventory-Aware Menu Optimization :

- Reduce $220,000 in ingredient inventory to $50,000

- Factor real-time inventory into menu generation

- Maintain nutrition and taste quality

Recipe Accuracy & Yield Intelligence :

- Resolve yield inaccuracies across 79,861 meal components

- Eliminate $500$2,000/week in waste

- Build AI-powered yield prediction that learns from production data

Healthcare-Grade Compliance (Future Horizon) :

The company is exploring Medicare and Medicaid partnerships for condition-specific meal plans.

Future requirements :

- HIPAA-compliant data handling

- Dietitian approval workflows

- Outcome tracking

- Architecture decisions today must support this direction.

AI-Specific Requirements :

- Architect reliable, cost-effective LLM API systems (Claude, GPT)

- Build AI tools usable by non-technical operators

- Design weighted scoring engines with explainable outputs

- Work with structured data (recipes, ingredients, biomarkers)

- Evaluate when to use LLM vs rule-based vs database query

- Integrate health data APIs (Apple HealthKit, Google Health Connect, FHIR)

Who You Are :

Technical excellence alone is insufficient.

Culture compounds :

- Hands on Keyboard : You write code daily.

- AI-Native : AI tools are core to your workflow.

- Trusted Autonomy : You do not need heavy management.

- Bias to Shipping : Build v1 fast, measure, iterate.

- Motivated by Mission : Personalized nutrition is meaningful and consequential.

- Strong Translator : You collaborate effectively with opinionated, non-technical founders.

- Low Ego, High Ownership : You take responsibility, accept feedback, and thrive in a direct, fast-paced environment.