Dedicated engineering pods

Dedicated engineering pods, embedded in your team

A small senior team that works inside your systems, your sprints, and your standups. Useful when you have more roadmap than capacity and want engineers who accumulate context rather than restart it every project.

Embedded teamElastic capacitySenior only
Quick answer

An embedded engineering pod with senior data and AI engineers working in your systems, your sprints, and your tooling, with elastic capacity month to month.

The roadmap is not capacity-constrained by ideas

Engineering demand does not arrive in neat, hireable increments. You need two engineers for eight months, then one, then three when a large client onboards. Hiring cannot follow that curve, and freelancers rebuild context every time. Meanwhile a project-based vendor produces exactly the scope in the statement of work and has no incentive to flag the thing they noticed that was not in it.

How a pod works

  • A named team of senior data or AI engineers, consistent month to month rather than rotating
  • Working in your repos, your ticketing system, your sprints, and your review process
  • Capacity adjustable with notice as your roadmap changes, up or down
  • Direct access to your team, not routed through an account manager
  • A technical lead who owns delivery quality and pushes back when a plan is wrong
  • Knowledge documented as it accrues, so context lives in your repo rather than in our heads

How we work

  1. Scope the roadmap and agree what the pod owns versus what stays with your team

  2. Start with two engineers on a real deliverable to establish working rhythm

  3. Adjust composition and size as the roadmap and priorities shift

  4. Review quarterly on shipped outcomes rather than hours logged

Typical stack

PythondbtAirflowSnowflakeBigQueryAWSReactTypeScript

Frequently asked questions

Staff augmentation places individuals who slot into your existing team structure and management. A pod is a small team with its own technical lead that takes ownership of a workstream, so you are delegating an outcome rather than directing individuals. If you want to manage the work yourself day to day, staff augmentation is the better fit and cheaper.

Three months, mainly because anything shorter is dominated by ramp-up and neither side gets value from it. After that it runs month to month with notice on capacity changes.

Yes, that is what dedicated means. Pod engineers are not shared across clients, because context-switching is exactly what makes outsourced engineering underperform.

It stays with you by design. Code lives in your repos, decisions are recorded, and runbooks are written as work happens rather than assembled in a final week. We also run handover sessions with whoever takes over.

Go deeper

Scope a pod

Tell us what is stuck in your roadmap and we will propose a pod size and composition.

Start a project

Proof from our work

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