Product acceleration
- Senior product engineer
- Backend / integration engineer
- Shared quality ownership
Engineering capacity planner
IT staff augmentation for the capability your roadmap is missing.
IT staff augmentation adds vetted engineers to your existing delivery organization while you retain product and technical ownership. FISTA matches capability, seniority, collaboration style, and system context across web, mobile, AI, data, platform, and blockchain work—helping leaders add integrated capacity without presenting unverified profiles, rates, rankings, or availability.
Role + capability matrix
Which engineering capability should you add?
Start with the system responsibility and delivery gap, then choose the title. A backend engineer for integration-heavy platform work needs different evidence from one focused on product APIs; an AI engineer needs evaluation and data judgment beyond model familiarity. FISTA uses this context to shape screening and present a credible match.
CapabilityEvidence to inspectTypical responsibility
Frontend / product UIReact, Next.js, accessibility, performanceCustomer-facing product delivery
Backend / platformAPIs, services, data, reliabilityCore systems and integrations
AI / agent engineeringRAG, orchestration, evaluation, toolsProduction AI workflows
MobileNative or cross-platform product engineeringiOS and Android delivery
Data / infrastructurePipelines, cloud, observability, operationsScalable delivery foundations
BlockchainSmart contracts, protocol services, reviewDecentralized infrastructure
Share the capability gap, system context, seniority, working model, and what success must look like inside your team.
Request matched engineersIllustrative compositions
What could an augmented team look like?
Team shape should follow the delivery bottleneck, not a fixed bundle. These examples illustrate how capability categories can combine; they are not named profiles, availability claims, rates, or guarantees. Discovery may reveal that one senior specialist is more useful than a larger generic team.
AI workflow pod
- AI / agent engineer
- Platform or data engineer
- Client workflow owner
Platform reinforcement
- Backend / platform engineer
- Data or infrastructure engineer
- Client technical lead
Transparent matching funnel
How does FISTA vet and match engineering capacity?
FISTA narrows from the role brief to relevant evidence: fundamentals and architecture for the responsibility, hands-on problem solving, communication, and team integration. The customer reviews the recommended fit and retains the decision. The funnel is transparent about what was assessed and avoids invented pass rates, rankings, or talent-marketplace theater.
- 01
Brief
Responsibility, context, seniority
- 02
Evidence
Relevant systems and decisions
- 03
Technical
Depth and judgment for the role
- 04
Collaboration
Communication and team fit
- 05
Client review
Transparent recommendation and decision
Integration + continuity
How do augmented engineers become part of the delivery system?
Integration begins with access, standards, architecture context, decision rights, and a named client owner. Early work is reviewed against the team’s real quality bar; communication and feedback are explicit. Continuity is supported through shared documentation and knowledge flow, while any staffing change is handled through the agreed engagement process—not a blanket replacement promise.
- 01
Before start
Access plan, standards, responsibilities, working cadence
- 02
First working cycle
Pairing, repository context, bounded contribution, feedback
- 03
Integrated delivery
Normal planning, review, release, and operating ownership
- 04
Continuity
Documentation, knowledge sharing, explicit change process
Role request summary
Add the capability your delivery system can integrate.
Responsibility
The system or outcome this person must own
Evidence
The technical judgment you need to inspect
Working model
Cadence, overlap, decision rights, communication
Continuity
Duration, documentation, and knowledge flow