AI Applied Engineers
Fewer Engineers. Faster Delivery. Knowledge That Stays With You.
We pioneered the AI Applied Engineer — a new category of technologist who delivers what traditionally required multi-person teams, while ensuring institutional knowledge stays with your project, not our consultants.
Traditional Consulting Has a Knowledge Problem
When your consulting engagement ends, the knowledge walks out the door. Large teams create dependency. Platform-first approaches leave you locked into proprietary systems.
You're left with delivered code but no understanding of how it works or how to extend it.
Large teams mean diffused accountability and communication overhead
Institutional knowledge leaves when consultants leave
Platform-centric approaches create vendor lock-in
Introducing the AI Applied Engineer
An AI Applied Engineer is a senior technologist who leverages AI tools to multiply their individual capability — delivering outcomes that traditionally required a full team, while ensuring knowledge transfers to your organization.
This isn't about replacing engineers with AI. It's about amplifying exceptional engineers so they can do more, faster, with complete transparency.
The AI Applied Engineer Role
An AI Applied Engineer:
- Operates across the full development lifecycle — architecture, implementation, testing, deployment
- Uses AI coding assistants, agents, and automation as force multipliers
- Delivers production-ready code with comprehensive documentation
- Transfers knowledge continuously, not just at project end
- Works as a transparent partner, not a black-box vendor
From Discovery to Delivery
Discovery
We assess your needs, existing systems, and goals. No generic proposals — we scope based on your specific situation.
1-2 daysRapid Prototyping
Your AI Applied Engineer delivers a working prototype or proof-of-concept, not a slide deck. You see real progress within the first week.
1-2 weeksIterative Delivery
We build in focused sprints with continuous deployment. You have visibility into every commit, every decision, every tradeoff.
2-8 weeks typicalKnowledge Transfer
Documentation, architecture decisions, and operational knowledge transfer to your team. We don't leave until your team can own it.
Included in every engagementAI Applied Engineers vs. Traditional Consulting
| Dimension | Traditional Consulting | AI Applied Engineers |
|---|---|---|
| Team Size | 5-10 person teams | 1-2 engineers |
| Delivery Model | Platform-centric, methodology-heavy | People-centric, outcome-focused |
| Timeline | 12-16 weeks typical | 2-4 weeks typical |
| Knowledge Retention | Leaves when we leave | Transfers to your team |
| Transparency | Weekly status reports | Real-time visibility |
| Cost Structure | Headcount-based billing | Outcome-based engagements |
Common Engagement Types
Legacy Modernization
Migrate legacy systems to modern architectures. What traditionally takes 12-16 weeks with a full team, we deliver in 2-4 weeks with one AI Applied Engineer.
MVP & Product Development
Go from idea to production-ready MVP. We build fast without cutting corners on code quality, testing, or documentation.
AI Integration
Add AI capabilities to your existing products. From LLM integration to custom ML models, we implement AI that delivers real business value.
Nordic AI Engineering Expertise
FrostLogic defined the AI Applied Engineer role. We're not adapting to AI — we built our practice around it from day one. As a Nordic company, we bring Scandinavian engineering values: transparency, quality, and respect for your time.
Proven track record across industries
We measure what matters
Malmö-based, your timezone, your language
Your code, your data, your IP. Always.
Ready to Work Differently?
Let's discuss how an AI Applied Engineer can accelerate your next project.
Or email us at hello@frostlogic.se
Frequently Asked Questions
A contractor fills a seat on your team. An AI Applied Engineer delivers outcomes — complete features, working systems, transferred knowledge. We're accountable for results, not hours.
Our engineers use a combination of AI coding assistants (GitHub Copilot, Cursor, Claude), automated testing tools, and custom AI agents. The specific toolkit depends on your tech stack and requirements.
Every deliverable includes comprehensive test coverage, documentation, and architect-level review. We don't sacrifice quality for speed — AI lets us have both.
We offer maintenance and support packages. But more importantly, our knowledge transfer process ensures your team can own and extend the codebase independently.
Your data stays yours. We don't train AI models on client code. All IP created during the engagement belongs to you. We're happy to sign NDAs and work within your security requirements.