When does your team need AI staff augmentation?


Your roadmap is growing, but your team isn’t

A senior AI engineer typically takes 3-6 months to hire, onboard, and bring to full productivity. Sprints don’t wait that long. We place vetted AI/ML engineers within 1-2 weeks: specialists already proficient in your tools and delivery standards, so onboarding takes days, not months.

You have a specific skill gap that doesn’t justify a full hire

You need NLP expertise for one workstream, or an ML engineer for a single model integration. A full-time hire for bounded scope adds salary, benefits, and ramp time you don’t need. Our model brings in exactly the capability required, for exactly as long as you need it.

AI tooling is in your pipeline, but adoption is inconsistent

Copilots and code generation tools are already in your pipeline, but delivery timelines haven’t moved because usage is inconsistent across the team. Our engineers apply AI tooling: copilot-assisted development, automated code review, AI-generated test scaffolding as a structured, consistent part of delivery.

You’re entering a new AI domain without internal expertise

You’re building a recommendation engine, a document intelligence layer, or an LLM-powered workflow for the first time. Your team knows the product but not the AI domain. We bring in specialists who’ve already built in that domain and transfer knowledge as part of the engagement, so you reach a working system faster and build internal capability along the way.

6K7A9888 scaled

What AI-assisted engineers deliver differently

dobasevych new new

“There’s a version of AI augmentation that just means you have more people with access to ChatGPT. That’s not what we build.

Our engineers use AI tooling as a structured part of their workflow — copilot-assisted development, automated code review, AI-generated test coverage — applied consistently and reviewed rigorously.

The result is faster delivery, earlier risk detection, and production-ready output. The AI handles the repetitive work. The engineer handles the judgment. That’s the combination that actually moves your roadmap.”

Oles Dobosevych
Head of Data Science/Data Engineering

What your team achieves with Geniusee AI augmentation


Start with a focused engagement to close a specific gap, or bring in a sustained augmentation team to accelerate a broader roadmap. Here is what these engagements produce in practice.

30–40% faster delivery on comparable sprints

AI copilots handle repetitive coding, test scaffolding, and documentation, freeing engineers to focus on architecture and product logic. Teams we augment ship 30–40% faster on a comparable scope. For Imagine AI, applying AI to the right repetitive workflows cut manual hiring effort by 85% and made candidate search up to 90% faster.

Photo 11
Photo 9

50% faster data processing without rebuilding your stack

For Alvarez & Marsal, we built a TigerGraph-powered logistics platform unifying dispatch, routing, and oversight, with streamlined ETL cutting data processing time by 50%. Our engineers delivered that result inside the client’s existing data architecture, not around it.

Production-ready code, every sprint

Every AI-generated artifact goes through rigorous human review before it reaches your codebase. We operate under ISO 27001 standards and AWS partnership requirements — so your security posture, compliance framework, and audit trail stay intact regardless of how much AI tooling sits in the delivery pipeline. You can see this in practice in our work with Forethought and Factmata.

image 6

Capability transfer built into the engagement

Our engineers document what they build and explain the decisions behind it, working alongside your team rather than in a black box. When the engagement ends, your team understands the system and has absorbed working patterns from engineers who use AI tooling well.

Specialists 1

IT experts are ready to start building AI PoC for you

Mask group
Tested across 7 Geniusee departments

Check if your AI idea is worth building

Download the whitepaper to evaluate AI use cases, set value gates, validate PoCs, and scale only the workflows that prove measurable value. Includes readiness score, use case framework, PoC validation steps, governance, and scaling roadmap, based on Geniusee’s internal AI transformation, where one workflow saved up to 120 hr/month.

Thank you!
Message sent successfully!

How we run an AI staff augmentation engagement


From first call to first commit, a structured process that gets the right people into your team fast and keeps them productive throughout.

Photo

Strategic needs assessment

We align with your objectives, scope, and risk profile, then map the capability gaps in your current setup. We draft role definitions, success metrics, and technical requirements for every position, so the engineers we place match what you actually need.

NDA execution

A bilateral NDA goes into place immediately, protecting all data, documentation, and intellectual property before any information is shared.

Expert selection

Our talent team curates candidates through in-depth technical assessment, domain screening, and culture-fit interviews. You see the final shortlist and confirm alignment before anyone starts. Typically, 1–2 weeks from needs assessment to approved candidate.Our talent team curates candidates through in-depth technical assessment, domain screening, and culture-fit interviews. You see the final shortlist and confirm alignment before anyone starts. Typically, 1–2 weeks from needs assessment to approved candidate.

Compliant hiring

We handle employment contracts, compensation, and mandatory filings across jurisdictions — full compliance with labor laws, tax requirements, and your own governance policies. You don’t manage the employment relationship; you manage the work.

Clear onboarding and oversight

Chosen specialists receive domain orientation, toolchain access, and security credentials on day one. Structured check-ins and performance reviews keep deliverables on track throughout the engagement. You have visibility into progress without managing the operational overhead.

Our success in numbers

Genuisee’s versatile experience, gained over more than 8 years, has enabled us to form a team with a proven track record.


Geniusee 195 1 2

20+

Countries

200+

Projects completed

80

NPS score

300+

Industry-specific experts

Why choose Geniusee for AI staff augmentation services?

What we bringWhat it means for your business
• 200+ completed projects since 2017• 300+ cross-functional engineersYou leverage a stable, battle-tested software partner with a global footprint across 20+ countries, minimizing vendor risk.
• AWS Advanced Tier Partner• Dedicated AI/ML, NLP, and GenAI specialistsNo onboarding lag. Specialists align with your exact tech stack and begin shipping production-ready code within 1-2 weeks.
• ISO 9001 & ISO 27001 Certified• ISTQB-certified QA protocolsTotal data security and structural integrity. Every AI-assisted artifact undergoes human review to safeguard your codebase.
• Fixed Scope, T&M, or Dedicated Teams, Full-lifecycle supportPay only for the capacity you need. Scale resources dynamically without adding long-term salary or benefits liabilities.

Recognition, certifications, and partnership


logo aws

Certified AWS Partner delivering secure, scalable cloud-native solutions.

logo iso

ISO-compliant processes ensuring quality, security, and reliability.

logo plaid

Trusted integration partner for financial data connectivity and open banking.

logo istqb

Team of ISTQB-certified QA engineers for world-class software testing.

logo 5 1

Consistently rated ★5.0 by clients for reliability and delivery excellence.

logo 5

Accredited partnership supporting advanced testing and continuous QA automation.

Frequently asked questions


What is AI staff augmentation?

AI staff augmentation means extending your existing team with external engineers who use AI tooling — copilots, automated code review, NLP models — alongside their own expertise to deliver faster, at lower cost, without sacrificing quality.

How quickly can augmented engineers start?

Most engagements reach the onboarding stage within 1–2 weeks of final candidate approval. Our structured process (needs assessment, vetting, NDA, compliant hiring) is designed to remove friction at every step.

How does AI staff augmentation differ from standard outstaffing?

Standard outstaffing provides additional headcount. AI-augmented staffing provides headcount plus AI tooling, validated workflows, and senior oversight — so you get measurable productivity gains on top of the extra capacity. See how our dedicated team model works.

What industries do you work in?

Primarily fintech, edtech, retail, and enterprise SaaS — though our engineers cover a wide range of domains. If you have a niche requirement, we will let you know upfront whether we can meet it.

How do you protect our IP and data?

A bilateral NDA is signed before any information is exchanged. We operate under ISO 27001 standards and are fully compliant with relevant data protection regulations, including GDPR.

What pricing models do you offer?

We offer flexible engagement models: Fixed Scope for bounded deliverables, Time & Materials for evolving requirements, and Dedicated Teams for sustained augmentation. You pay for the capacity you need without long-term employment liabilities.