Hire AI-Augmented Senior Engineers. Embedded in Your Team in 2 Weeks.
L5+ engineers fluent in Claude Code, Cursor, and agentic workflows — dropped into your repo, your Slack, your standups. Built for Series A founders who need senior capacity faster than hiring allows.
You raised on a vision. The clock to Series B is real, and senior engineering is the constraint that doesn't bend to a deadline.
1
Senior engineering hires take 3–6 months end-to-end.
2
Your existing team is heads-down on the core product.
3
AI features keep landing in the backlog instead of in production.
Your team keeps moving the core product. We bring senior, AI-augmented engineers in alongside, and start shipping the rest in parallel.
The Model
Built for Founder Speed
We drop senior, AI-augmented engineers into your team. Same Slack, same repo, same standups — just with the output of a team twice the size, on day one.
01
Scope & Align
30-minute fit call, scope shared with you in writing, NDA signed. No deck-shop runaround.
02
Embed the Team
L5+ engineers in your repo, your Slack, your standups — onboarded in ~2 weeks from kickoff.
03
Ship in Week 2
First PR landed by end of week 2. Features in staging by week 3. Weekly releases from there.
04
Stay Long Enough to Own It
3–12 month engagements, scaling team size with you. We stay until production outcomes are owned.
3–12 month engagement
No re-org. No vendor friction. No "AI initiative" that never ships.
What an Embedded Team Ships
What You'll Get Done First
A snapshot of typical Series A engagements — your actual roadmap is yours. We slot into whatever's already in your sprint.
AI Strategy & Roadmapping
Where to add AI in your product, in what order, with what risk. From a team that's done it across 200+ engagements.
LLM & Agent Systems
Copilots, RAG over your docs, agentic workflows. Production-grade with observability — not demo-grade.
Data Infrastructure
The pipelines and storage your AI features actually need before they can perform reliably under real traffic.
MLOps & Deployment
From notebook to production: CI/CD, monitoring, rollback, observability. The boring part that decides whether AI actually ships.
AI Cost Optimization
Caching, batching, smaller model routing, fine-tuning when it pays off. Stop bleeding budget on every-token-to-GPT-4.
Workflow Automation
Internal tools that take real headcount off your roadmap — sales ops, support triage, ops dashboards, onboarding flows.
Why Magic Powered
Built for Founders Who Need to Ship Now
Senior-Only Talent
L5+ engineers with 7+ years shipping production systems. No juniors hidden in a "team rate".
AI-Native, Not AI-Curious
Our engineers live in Claude Code, Cursor, and agentic workflows daily. They bring 2–3× their solo velocity into your team.
In Your Repo in 2 Weeks
Pre-vetted bench of 150+ engineers. From kickoff call to first PR in two weeks — not two quarters.
Plug In, Don't Take Over
We work inside your Slack, your repo, your sprint. Your CTO stays in charge. We're capacity, not consultants.
Stay Long Enough to Own Outcomes
3–12 month engagements. Long enough to ship and own production, short enough to match a Series A runway.
Predictable Monthly Pricing
$30K–100K/month flat, scaled to team size. No hourly billing surprises, no overage drama.
Industries
Production AI in Real-Data, High-Stakes Domains
Your messy stack and ambitious data won't surprise us. We've shipped here over 200 engagements:
Federated ML Infrastructure for Healthcare Provider
Modernized legacy Java system and implemented federated learning with trusted execution environments at national scale.
MillionsPatient records secured
FullFederated ML in production
The Talent
Senior Engineers Who Plug In — Not Take Over
Every engineer is L5+ with 7+ years of production experience. They use Claude Code, Cursor, and agentic workflows daily — and they bring that velocity into your team from week one.
Production experience shipping AI features at scale
Fluent in modern AI tooling — Claude Code, Cursor, agentic workflows
Comfortable in a founder's Slack, not a partner's boardroom
M
Mykhailo
Senior Backend Engineer · 13 years exp.
L5+
Senior backend engineer with deep microservices and modernization experience. Most recently led the monolith-to-microservices migration at Porsche. Recent solo work: shipped an entire Temporal-orchestrated fintech backend using AI-assisted development.
Principal Engineer · Backend & Platform · 12+ years exp.
L6
Principal engineer with 12+ years across backend systems, cloud infrastructure, and platform reliability. Currently leading large-scale migrations from Cloud Run to Kubernetes with compliance-driven recovery testing. Strong on data platforms (BigQuery, Pub/Sub), GitOps with ArgoCD, AI/LLM integration, and full observability.
Senior Full-Stack Engineer · AI & Data · 8 years exp.
L5
Full-stack engineer focused on AI integration and large-scale data systems. Designed healthcare data-lake analysis on GCP, BigQuery, and Trino. Recent work: AI-powered tooling using OpenAI and Claude, payment systems, and indexing platforms. Strong across backend and frontend.
Polyglot backend with deep data engineering experience. Led teams of 5–6 engineers building distributed ETL pipelines and high-volume analytics platforms. Recent work: AI code-migration agents built on LangChain + LlamaIndex + Chroma.
Senior Engineer · Backend & DevOps · 18 years exp.
L6
Eighteen years across backend, cloud infrastructure, and distributed systems. Owned production reliability on Azure — full CI/CD, Kubernetes, and incident response. Earlier work spans data visualization, analytics platforms, multicast streaming backends, and mobile (iOS / Android).
Backend for high-throughput data systems and distributed platforms. Built Kafka and Spark pipelines for major automotive OEMs including BMW and Audi. Currently working on data indexers and L2 infrastructure. Comfortable across Java, Spark, and the modern data stack.
Building data-heavy SPAs and front-end interfaces for over a decade. Tech lead on ML-driven data visualisation platforms and AI test tooling. Lives in React, TypeScript, and D3 — equally comfortable on React Native for mobile.
Front-end team lead across healthcare platforms, enterprise monitoring tools, CDN admin tooling, and most recently maritime AI analytics. Specialises in design-system architecture and leading delivery teams from kickoff to launch.