Engineering Leader · Open to Relocation
Craig Campbell
Engineering technical leader with 15+ years of experience building high-performing teams, delivering 0→1 products, and embedding AI into engineering operations.
Known for translating complex technical concepts into business outcomes, driving alignment across product, engineering, and executive stakeholders, and developing engineers into future leaders. Hands-on track record with RAG-based AI systems, LLM integration, SOC 2 compliance, and large-scale infrastructure modernization.
Targeting Director of Engineering or Senior Engineering Manager roles at growth-stage or mission-driven companies where AI adoption, team development, and scalable execution are strategic priorities.
What I found has real implications for anyone building AI-powered products: the gap between frustrating and impressive AI experiences isn't model quality. It's architecture. Memory, consistency, and cost are all solvable engineering problems.
Read on LinkedIn →Every week, someone on our team was manually tracking EV incentives across government websites, utilities, and state programs. It was time-consuming, error-prone, and didn't scale. So we built a system to replace it.
Read on LinkedIn →A personal RAG application that indexes Obsidian notes for semantic search and LLM-powered Q&A — built for my own knowledge management workflow.
- Inherited an ownerless codebase and established architecture standards, documentation, and team ownership frameworks.
- Architected a RAG-based AI monitoring system (Firecrawl, PostgreSQL, Anthropic) — incentive-change detection 10%→90%, co-founder research 8 hrs/week→15 min; monitors 443 programs across 46 states.
- Built loan origination integrating Plaid and KBB — processing 6 hours→30 minutes (~80%) for a 5-person team at 50+ applications/week.
- Led SOC 2 Type 2 readiness (25+ policies, 200+ controls) and responsible AI practices (MCP integrations, prompt quality standards).
- Led an 8-person team (6 engineers + 1 designer), replacing ad-hoc Notion tracking with Scrum and tooling — stronger sprint predictability and delivery visibility.
- Drove full AWS migration consolidating two platforms — ~$2,500/mo hosting savings, ~20 hrs/week dual-platform maintenance eliminated, email/SMS failover reliability improved 90%+.
- Achieved SOC 2 Type 2 certification from scratch.
- Co-founded a philanthropic giving platform — strategy and full technical architecture.
- Shipped an MVP with 3 engineers + 1 designer that mobilized $2M+ in donations, including Ukraine relief.
- Established 5 B2B partnerships (Bain LA, Insight Partners, and others).
- Modernized legacy Rails/Slim to Node.js + React — ~30% faster feature delivery.
- Built a software practice from scratch — 6 engineers, $1.25M annual budget, 5 concurrent projects.
- Delivered ECHO Colorado's unified platform — 7 fragmented apps → one system for 10,000+ in-state users; licensed to Oregon and Idaho (+5,000 users).
- Led CDC-funded dental evaluation platform for the Colorado Dept. of Public Health.
- Grew portfolio to $5M+ (10 major contracts, 40+ engagements); mentored 3 engineers to internal promotions (2 Lead, 1 Manager).
- Senior and lead roles across fintech, enterprise, and high-traffic consumer — architecture, mentorship, CI/CD, agile delivery, requirements.
- At Match.com: daily email runs 24+ hours→~3 hours; custom CMS for content in 26 languages.
I think about engineering at the level of the business, not just the backlog.
Engineering strategy is business strategy. I work backwards from what the company needs to win, not forward from what's technically interesting. That means making tradeoffs explicit, sequencing investments deliberately, and knowing when the right call is to slow down versus push for velocity.
The org chart is a product decision. How a team is structured shapes what it can build and how fast. I think carefully about team topology, where to centralize, where to give autonomy, how to avoid dependencies that create bottlenecks and I revisit it as the product evolves.
AI adoption without guardrails is a liability, not a feature. I've shipped production AI systems and built the practices around them — prompt quality standards, MCP server policies, code review guidelines for AI-generated output, and SOC 2 controls that account for AI tooling risk. The teams I build move fast with AI because they've done the unglamorous work of building the guardrails first.
Technical vision has to be legible to the business. I translate between engineering and the rest of the organization, turning ambiguous product goals into architectural decisions, and making technical tradeoffs clear to executives without requiring them to understand the implementation. That's the job.
Process only works if engineers trust it. I've introduced Scrum into teams that had none, and it only landed because I treated it as a communication tool, not a mandate. The goal is always visibility and predictability for the team, for product, for leadership, without adding overhead that slows people down. When process serves engineers, they defend it. When it doesn't, they route around it.
The best engineering investment is the engineers themselves. Three of the engineers I've managed have been promoted into lead or manager roles. I take that seriously — running 1:1s focused on growth, not status, and creating real opportunities for people to stretch into harder problems. A team that develops its own leaders compounds in ways that hiring alone never can.
Let's build something together.
Open to Engineering Manager and Director of Engineering opportunities.