Senior AI & DevOps Capacity, Without London Day Rates.
The UK tech talent shortage isn't closing — and London day rates for senior DevOps and AI engineers reflect exactly how scarce that talent has become.
We embed pre-vetted specialists directly into your existing sprints, tools, and codebase — not a siloed offshore team working in isolation.
What's Included — In Detail
AI & Machine Learning Talent
- ✦LLM engineering & integration — connecting large language models into production applications
- ✦Agentic AI development — autonomous workflow and AI agent architecture
- ✦NLP & applied ML specialists — model development, fine-tuning, and deployment
- ✦AI chatbot & automation engineers — customer-facing and internal automation builds
- ✦Data science support — model evaluation, data pipeline architecture
DevOps & Infrastructure Talent
- ✦CI/CD pipeline architecture — build, test, and deployment automation
- ✦Cloud infrastructure engineers — AWS, Azure, GCP environment design and management
- ✦SRE (Site Reliability Engineering) — uptime, monitoring, and incident response capability
- ✦Containerization & orchestration — Docker, Kubernetes deployment and management
- ✦Security-conscious infrastructure — DevSecOps practices built into the pipeline, not bolted on after
How Integration Actually Works
- ✦Direct access to your existing repo, ticketing system (Jira/Linear), and communication tools (Slack/Teams)
- ✦Daily standup participation within your working-hour overlap window
- ✦Code review and PR workflows identical to your internal team's process
- ✦No "black box" offshore delivery — full visibility into what's being built and how
Why UK Businesses Choose This Model
Bypass the 8-12 week UK technical hiring cycle for scarce skill sets.
Senior-level capability at a cost structure that doesn't compound London's engineering salary inflation.
4-5 hour working overlap with London — same-day collaboration, not overnight handoffs.
Flexible scope — a single specialist for a defined project, or a full pod for sustained capacity.
Direct integration into your existing tooling, not a parallel system.
Who This Is For
Engineering teams with a critical role that's been open for months.
Companies building AI capability who don't have in-house ML/LLM expertise yet.
Businesses needing to scale DevOps/infrastructure capacity for a specific migration, build, or scaling event.
Frequently Asked Questions
Will this replace our in-house engineering team?
No — the model that works best is augmentation, not replacement. Most clients use an offshore pod to absorb a defined technical workstream while their core UK team focuses on work that benefits from being in the room.
How do you vet AI and DevOps talent before deployment?
Every specialist goes through technical assessment specific to the discipline (not a generic screening), plus a portfolio/production-experience review before being matched to a client engagement.