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Case Study · AI/ML Leadership

Fractional
AI/ML Developer:
Scaling Engineering &
Launching 3 AI Products

How AdmireTech's Fractional AI/ML Developer helped a Series A SaaS startup scale from 8 to 35 engineers, define a complete AI strategy, and ship three production AI products — all in 12 months at 40% of a full-time hire cost.

SaaS MarketplaceSeries A · $8M RaisedAI/ML StrategyTeam ScalingLLM Integration12-Month Engagement

Engagement Outcomes

8 → 35
Engineers Scaled
3
AI Products Launched
12
Months Engagement
40%
Cost vs Full-Time CTO
27 Engineers Hired & Onboarded
100% Engineering Team Retention
3× Developer Productivity via Internal AI Tools
Series B Ready in 12 Months

The Project

A $8M Series A startup — funded but leaderless

The Challenge

CTO departure left a critical leadership vacuum at the worst time

A Series A SaaS marketplace had raised $8M and was under enormous pressure to ship, scale, and demonstrate AI differentiation. Their founding CTO had departed, leaving an 8-person team without technical direction during the most critical growth phase.

The board couldn't justify a $300K+ full-time CTO salary at this stage — but they desperately needed the leadership.

  • No AI strategy or roadmap — competitors were pulling ahead
  • Engineering team directionless — morale and velocity declining
  • No hiring process, engineering ladder, or culture framework
  • Technical debt accumulating while investors expected new features
  • Board needed credible technical leadership for Series B preparation

The AdmireTech Solution

A Fractional AI/ML Developer — 20 hours/week, full CTO-level impact

AdmireTech deployed a senior Fractional AI/ML Developer with 15+ years of engineering leadership and deep production AI expertise. Operating 20 hours per week across three simultaneous workstreams.

This wasn't advisory — our developer shipped code, made architecture decisions, conducted interviews, presented to the board, and mentored internal tech leads.

  • Immediate AI-first technical direction and architecture decisions
  • Structured hiring — 27 engineers onboarded with zero mis-hires
  • Three AI products scoped, built, and shipped to production
  • Engineering ladder, culture, and CI/CD built from scratch
  • Series B pitch deck technical narrative written and board-presented

Engagement Structure

Four parallel tracks running simultaneously

Rather than tackling problems one at a time, AdmireTech ran four workstreams in parallel — ensuring no part of the business fell behind while another was being strengthened.

Team Building

Recruited, interviewed, and onboarded 27 engineers across frontend, backend, and ML. Built engineering ladder, performance review frameworks, and career development paths from scratch.

Process & Culture

Implemented agile practices, code review standards, CI/CD pipelines, and technical documentation. Instilled an AI-first engineering mindset that outlasted the engagement.

AI/ML Strategy

Defined the complete AI product roadmap, evaluated LLM integrations, built ML infrastructure on AWS, and guided three AI-powered features from first prototype to production launch.

Technical Leadership

Architected scalable distributed systems, managed vendor relationships, presented technical roadmaps to investors and the board, and mentored internal tech leads for long-term succession.

Implementation Timeline

12 months. Four phases. Zero disruption.

Phase 1 · Months 1–3

Foundation
  • Full technical audit — code, infrastructure, debt
  • First 8 engineers hired and onboarded
  • Core engineering processes established
  • AI product vision and roadmap defined

Phase 2 · Months 4–6

Scale Up
  • Team grows to 20 engineers
  • CI/CD pipelines and ML infrastructure live
  • AI Recommendation Engine shipped (Product #1)
  • Engineering culture fully established

Phase 3 · Months 7–9

Accelerate
  • Team reaches 30 engineers
  • AI Support Chatbot launched (Product #2)
  • Predictive analytics in active development
  • Internal AI dev tools deployed — 3× productivity

Phase 4 · Months 10–12

Handoff
  • Full team at 35 engineers
  • Predictive Analytics live (Product #3)
  • Internal tech leads promoted — full succession
  • All processes documented for independence

Results Delivered

Every metric moved in the right direction

35

Engineers Hired & Onboarded

3

AI Products Shipped to Production

40%

Cost vs. Full-Time CTO Hire

100%

Engineering Team Retention

Our Fractional AI/ML Developer from AdmireTech didn't just fill a seat — he transformed our entire engineering organisation. He built a team that could function without him, which was exactly what we needed. The AI products launched under his guidance became our key differentiator in Series B discussions.

JM
Jordan M.
CEO, SaaS Marketplace Platform

AI Products Launched

Three production AI features — shipped in 12 months

Product 1 · Month 6

AI Recommendation Engine

Personalised product recommendations built on collaborative filtering and LLM-based semantic matching. Surfaces the most relevant marketplace listings based on user intent and behaviour.

↑ 34% Conversion Increase

Product 2 · Month 9

AI Support Chatbot

24/7 intelligent support chatbot trained on product documentation and historical tickets. Integrated with Zendesk for seamless human escalation, resolving 60% of inquiries without agent involvement.

60% Inquiries Automated

Product 3 · Month 12

Predictive Analytics Dashboard

ML-powered dashboard predicting customer churn, revenue forecasting, and inventory optimisation signals. Became a flagship feature in enterprise sales pitches and Series B conversations.

Key Series B Differentiator

Internal Tools · Ongoing

AI-Assisted Developer Tooling

AI-assisted code review, automated testing pipeline, and documentation generation. Reduced code review time by 60% and tripled overall developer throughput across the engineering team.

3× Developer Productivity

Technology Stack

Modern AI-first architecture from day one

AI / ML
PythonTypeScriptOpenAI APILangChain
App
ReactNode.jsPostgreSQLRedis
Infra
AWSKubernetesTerraformGitHub Actions
Data
DatadogVector EmbeddingsML Pipelines

Frequently Asked Questions

Everything you need to know aboutFractional AI/ML Developers

Our Fractional AI/ML Developers provide part-time senior technical leadership — typically 15–20 hours per week. They define AI/ML strategy, architect production-grade systems, hire and mentor engineers, manage architecture decisions, and present to investors and boards. You get the same calibre of technical execution as a full-time senior hire at a fraction of the cost and commitment.

AdmireTech’s Fractional AI/ML Developer engagements start from $1,500/month depending on time commitment and scope. Compare this to a full-time senior AI/ML hire at $200K–$350K/year plus equity. You get the same calibre of leadership at 30–50% of the cost — with no long-term hiring commitment and no equity dilution.

A Fractional AI/ML Developer is the right choice when you: (1) Need AI/ML expertise but can’t justify a $250K+ salary, (2) Are scaling an engineering team rapidly and need experienced leadership, (3) Want to define and execute an AI strategy without permanent overhead, or (4) Need someone to build the team, processes, and products before hiring a full-time technical leader.

We build for independence from day one. Every engagement includes promoting and mentoring internal tech leads, fully documenting all processes and architecture decisions, and establishing engineering playbooks that allow the team to operate autonomously. The goal is always to work ourselves out of a job — and hand over a team that’s stronger and more self-sufficient than when we found it.

Hire a Fractional AI/ML Developer

Senior AI/ML leadership without the full-time price tag

AdmireTech's Fractional AI/ML Developers bring production-grade AI expertise, engineering leadership, and hands-on execution — exactly when and where you need it.

From $1,500/movs $250K–$400K/year
for a full-time hire
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