Product engineer · Growth engineer · Solo build
I turn complex problems into working systems.
I build across product, engineering, data and growth, from the underlying model to the interface and the systems that get it in front of people.
- Disciplines
- Engineering / Product / Data / Growth
- Mode
- Solo, end‑to‑end ownership
- Stack
- Full‑stack / User experience / AI
The loop
I don’t separate product, engineering and growth into handoffs. The problem, the system, the implementation and the distribution inform each other.
Strip the problem down to what actually needs to be solved. Understand the constraints, the users, and the information underneath it.
What I build
The boundaries between these disciplines are where most of the useful decisions happen. I work across them instead of handing them off.
Product engineering
From ambiguous requirements to a working product. I handle the interface, application logic, database, authentication, search, and deployment, while challenging features that don’t need to exist.
Systems & data
I design the underlying model before building around it: entities, relationships, constraints, pipelines, and the structures that determine what the product can become.
Growth engineering
I treat distribution as a system. Acquisition becomes data, data becomes automation, and automation becomes a repeatable source of demand.
AI & discoverability
I build products for both human users and machine retrieval, from technical SEO and structured data to AI search, citations, and agent access.
Product clarity
I reduce complicated products to the idea that actually matters. Positioning, naming, copy, and interfaces should make the underlying product easier to understand, not add another layer of explanation.
Skills
The working set across product, engineering, data and growth.
- Application development
- Interface systems
- Search & filtering
- Landing pages
- A/B testing
- Accessibility
- Server-side architecture
- API design
- Authentication
- OAuth
- Account systems
- Deployment
- Schema design
- Data modeling
- Database migrations
- Data pipelines
- Enrichment
- Web scraping
- Analytics
- Cold email
- Outbound infrastructure
- Domain separation
- Intent signals
- Lead scoring
- Target-list generation
- Competitor monitoring
- Attribution
- SEO architecture
- Structured data
- AI search optimization
- MCP integrations
- Crawl control
- Domain management
- DNS & routing
- Hosting & deployment
- Email infrastructure
Toolkit
What I actually reach for, not everything I’ve touched once.
- JavaScript
- TypeScript
- React
- Next.js
- Angular
- Node.js
- PHP
- SQL
- MySQL / PostgreSQL
- REST APIs
- Vite
- Tailwind CSS
- CSS / SASS
- HTML
- Supabase
- Netlify
- Cloudflare
- WordPress
- Framer
- Stripe
- Git / GitHub
- Gmail API
- OAuth
- Resend
- Retool
- PostHog
- Google Analytics
- Zapier
- Klaviyo
- OpenAI API
- Claude API
- Exa API
- Vercel AI SDK
- MCP
- Cursor
- Claude Code
- Figma
- Adobe Photoshop
- Adobe Illustrator
Selected work
Projects built alone, where the whole method runs at once.
Verscia
websiteThe obvious description is a platform for finding event vendors. That undersells the architecture. A directory answers “who provides AV in Las Vegas?” A structured system answers which companies hold a capability, where they operate, what equipment they carry, what affiliations they hold, which markets are dense, and how those companies relate to each other.
Built: Frontend, backend, design, provider data model, category semantics, onboarding and business claiming, search infrastructure, SEO architecture and AI-accessible data. No backend engineer, no DevOps, no SEO consultant, no copywriter waiting to be briefed.
The interesting shift was realizing the dataset is the product. Once enough structure exists, the database starts producing second-order information that isn’t stored anywhere: directory becomes database becomes intelligence layer.
- Owned
- Product, data, growth, copy
- Moat
- Data density & structure
PCM Tracker
The obvious description is a portfolio P&L tracker. That undersells the architecture. It replaced a legacy PHP system for a $3.7B hedge fund with an automated financial data pipeline that ingests portfolio extracts (positions, ROE), pulls live market pricing, validates incoming data, calculates P&L and ROE, and pushes updates to the dashboard in real time.
Built: Frontend, backend, database architecture, authentication, portfolio and equity data models, OAuth and ingestion, market pricing pipeline, data validation, realtime updates, admin tooling, audit logging, migrations, and deployment. Essentially the entire operational system, rebuilt solo.
The interesting shift was realizing this isn’t really a dashboard. It’s an automated system of record sitting between raw financial data and portfolio decision-making. The UI is just the final layer.
- Owned
- Product, engineering, data, infrastructure
- Moat
- Operational automation & data integrity
Persocrat
websiteThe obvious description is an AI persona simulation SaaS. That undersells the architecture. Persocrat models personas, traits, ICPs, concepts, buyers, customers, and projects, then runs simulations across configurable AI providers while handling billing, collaboration, permissions, research, and persistent structured outputs.
Built: Frontend, backend, database architecture, authentication, persona and trait system, ICP builder, AI simulation engine, multi-model and BYOK architecture, research pipeline, projects and collaboration, Stripe billing, trials, transactional email, PDF exports, RLS, migrations, and deployment. Essentially the entire SaaS product.
The interesting shift was realizing the AI isn’t really the product by itself. The product is the structured behavioral model around the AI. Personas, traits, ICPs, concepts, and simulation results create a persistent system that makes the model useful, reusable, and increasingly configurable.
- Owned
- Product, engineering, AI architecture, data, infrastructure
- Moat
- Structured behavioral data & simulation
Other projects
Earlier work built across different roles, teams, and organizations.
Roshel
Custom website for Roshel, a North American armored vehicle manufacturer serving clients including NASA, U.S. Homeland Security, and Canadian National Defence.
WebsiteForum
Custom website for Forum, an Alberta-based real estate developer with a $1 billion portfolio.
WebsiteFloorplan Navigator
SaaS widget that lets property prospects explore building floorplans, units, and details in 2D and 3D.
WebsiteMinto REIT
Custom website for Minto Apartment REIT, a real estate investment trust listed on the Toronto Stock Exchange.
WebsiteGreenwin
Custom website for Greenwin, an award-winning real estate management company.
WebsiteBroadstreet
Custom website for Broadstreet, a real estate developer with more than 11,000 apartment units across Central and Western Canada.
WebsiteCostSense
Custom website for CostSense, an accounting firm providing CFO and controllership services.
WebsiteNeighbourhood Explorer
SaaS widget using the Google Maps API to provide transit and business information around properties.
Website
Principles
A few rules I use when the right answer isn’t obvious.
01Maximize signal, minimize complexity
Every element has to earn its place, whether it’s a paragraph, a database field, or a settings screen. Complexity compounds through individually reasonable decisions.
02Delay what you can undo later
Don’t build for problems you don’t have yet. Expensive architectural decisions should be made when the product has earned the complexity, not before.
03Follow the consequences
A change that looks local rarely is. Trace what happens to the existing product, the data model, the user, the system at scale, and everything downstream.
04Optimize for business progress
A better product is not automatically a better business. When everything is a legitimate improvement, prioritize the change most likely to move the business forward.
Contact
Tell me what’s ambiguous.
I work best on problems that don’t yet have a clean shape: a product doing too many things, a dataset nobody can use, or a growth motion that still depends on manual work.
dami@damijohnson.com