Scaleups extending capacity
Your roadmap is bigger than your team. You need senior firepower without a 6-month hiring cycle.
Senior AI engineers, embedded in your team
Hire AI engineers who embed like in-house - without the 6-month search.
Senior engineers, full-time Ludotech employees, working from our Paris and Skopje offices. They join your standups, your codebase, your Slack - as if you had hired them yourself. On your timezone. Ready in weeks.
Hire proof
ShaprSeelkClient 03Client 04
Who this is for
Built for teams that need senior AI talent, fast
Teams missing AI specialists
Your engineers are great, but no one has shipped LLM features, RAG, or agents in production. You need someone who has.
CTOs avoiding the talent trap
You do not want freelancers with no commitment, and you do not want offshore staffing with no cohesion. You want hires who behave like hires.
Positioning
Not a marketplace. Not staffing. Something different.
| Dimension | Freelance marketplace | Offshore staffing | Ludotech |
|---|---|---|---|
| Engineer status | Contractor | Contractor or staff | Full-time Ludotech employee |
| Team cohesion | None - strangers per project | Variable | Built in - they work together daily |
| Timezone | Variable | Often async-only | Paris hours, with Skopje and Paris offices |
| AI fluency | Self-declared | Inconsistent | Required - every engineer ships AI |
| Time to start | 1-4 weeks | 4-8 weeks | 1-3 weeks |
| Commitment | Hourly, swappable | Project-based | Embedded, long-term |
Roles you can hire
Senior engineers across the AI stack
AI / ML engineers
LLM features, RAG, agents, evals, model integration.
Typical seniority: 5+ years, AI tooling fluent.
Full-stack engineers
React, Node, Python, product APIs, internal tooling.
Typical seniority: 5+ years, AI-assisted delivery fluent.
Backend engineers
Python, Go, Node, APIs, data workflows, performance.
Typical seniority: 5+ years, production AI feature exposure.
Frontend engineers
React, Next.js, React Native, design systems, product UI.
Typical seniority: 5+ years, AI UX patterns fluent.
DevOps / platform engineers
CI/CD, cloud infrastructure, observability, scaling, security.
Typical seniority: 5+ years, modern delivery workflows.
Tech leads / engineering managers
Technical direction, reviews, delivery rhythm, team coaching.
Typical seniority: 8+ years, AI product delivery context.
How embedding works
They join your team, not ours
1. Match
Match
We brief our team on your stack, product, and culture. We propose 1-3 engineers. You interview them like you would interview any hire.
2. Onboard
Onboard
They join your Slack, your repo, your standups, your tools. We do not insert a project manager between you. You manage them directly.
3. Ship
Ship
They work alongside your engineers, not in a parallel silo. PRs into your repo. Reviews on your timeline.
4. Scale
Scale
Add more engineers as needed. Same employer, growing team context. Ramp down cleanly when the work is done.
AI-native, concretely
AI fluency shows up in the work, not the pitch.
Production AI fluency
Engineers have shipped or contributed to LLM features, RAG systems, agents, or adjacent AI product work.
Modern development workflows
Cursor, Claude Code, code review discipline, eval-minded thinking, and fast iteration are part of the workflow.
Practical integration mindset
They fit AI features into your existing product, repo, observability, security, and release process.
Case studies
Teams we've extended
Hire
Shapr
Embedded engineering support for a growing product team.
- Team: senior Ludotech engineers embedded in the client roadmap and tools.
- Shipped: product features, AI modules, platform improvements, and release milestones.
- Outcome: velocity, feature throughput, retention, ramp time, or quality impact.
- CTO quote or video testimonial.
Hire
Seelk
Senior engineering capacity added to an existing team.
- Team: embedded engineers matched to the product, stack, and operating cadence.
- Shipped: roadmap-critical features and production improvements.
- Outcome: faster delivery, smoother ramp, and stronger engineering continuity.
- CTO quote or video testimonial.
Hire
Embedded team case
Longer-running embedded support for a team that needed senior AI-fluent firepower.
- Team: one or more Ludotech engineers working directly inside the client team.
- Shipped: AI features, product surfaces, backend systems, and operational tooling.
- Outcome: improved velocity, reduced hiring pressure, and reliable delivery capacity.
- CTO quote or video testimonial.
Pricing model
How we price embedding
Hire commercial structure
Monthly per engineer, with a minimum engagement length and clear replacement guarantees.
- Dedicated full-time engineer
- Ludotech support and continuity
- Replacement guarantee terms
- Scale up or ramp down cleanly
FAQ
Questions before you interview engineers
How fast can an engineer start?
Most matches can move from brief to interviews within weeks, depending on role and availability.
Are they really full-time on my project?
Yes. Embedded engineers are dedicated to your team for the agreed engagement.
What if the engineer is not a fit?
We stay close to the engagement and can adjust the match if the fit is not right.
Who manages them - you or us?
They join your operating rhythm and are managed day to day by your team, with Ludotech support behind them.
What is the minimum engagement?
Most embedded engagements are monthly and designed for meaningful ramp, delivery, and continuity.
What happens to IP and code?
Your product, repo, and code remain yours. Engineers work inside your tools and contribution process.
Can we hire them permanently later?
Permanent conversion can be discussed depending on the engagement and team setup.
How is this different from Toptal, Andela, or a freelance platform?
Ludotech engineers are full-time employees who work together daily, ship AI, and operate in European timezones.
Need senior AI engineers in your team?
Let's match.
Tell us your stack, roadmap, and timeline. We will propose the right senior profiles.