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Kuboid Logokuboid/Vinay Sheoran
[ FRACTIONAL CTO — AI-NATIVE ENGINEERING LEADERSHIP ]

I turn engineering chaos into discipline.

Fractional CTO for funded startups that need senior technical leadership — architecture, AI/LLM strategy, and engineering hiring — without a $300K/year hire. 10+ years, currently taking on 2-3 clients.

[ WORKED WITH ]
Token MetricsChange HealthcareMantra LabsContaqt.nlSkugal
[ 01 — THE PROBLEM ]

You don't have a CTO. You have a founder pretending to be one.

Architecture decisions get made ad hoc. Engineering hires don't work out. Your AI roadmap is more hope than plan.

And when investors ask hard technical questions, there's no one who can answer with real confidence.

// 01

No one owns architecture

Technical debt is swept under the rug until the system breaks at scale.

// 02

Hiring is a guessing game

Resumes look good, but tech interviews fail to weed out bad hires.

// 03

AI features are vibes, not a plan

Hype-driven wrappers replace sound agentic & RAG infrastructure.

// 04

Tech debt compounds silently

No guardrails or code reviews mean developers slow to a crawl.

[ 02 — WHAT I DO ]

Fractional CTO, full scope.

// 01

Technical Strategy & Roadmap

Translate business goals into a technical plan you can defend to investors.

// 02

Architecture & Code Quality

Review what's built, catch what breaks at scale, set standards before debt compounds.

// 03

AI/LLM Product Strategy

Production RAG pipelines and LLM agents I've actually shipped — not prototypes. What's real, what's hype.

// 04

Engineering Hiring & Team Building

Job specs, technical interviews, team structure that survives past 10 engineers.

// 05

DevOps & Infrastructure Cost Control

Cut cloud spend, fix the deploy pipeline, kill the 2am pages.

// 06

Investor-Facing Technical Narrative

Help you tell the technical story clearly in diligence and board conversations.

[ 03 — PROOF, NOT PROMISES ]

The discipline shows up in the numbers.

7.0s → 0.5s

Page load time, redesigned platform architecture (Token Metrics)

40%

Increase in deployment frequency, 15-engineer team (Token Metrics)

50%

Cloud infrastructure cost reduction (Skugal/InsurTech client)

800ms → 120ms

AI search latency reduction via semantic caching and query pruning

10M+

Daily database queries optimized with custom indexing and read-replicas

100+

Engineers hired, vetted, and onboarded across distributed teams

60%

LLM API cost reduction through structured output validation and model routing

18m → 2.5m

CI/CD build and test pipeline execution speedup, unblocking daily releases

Full breakdown of each project → See full profile
[ 04 — HOW WE'D START ]

No long contracts. No guessing.

01

Free 30-min discovery call

I learn your product, team, and where it actually hurts.

02

Week 1: Technical audit

Written assessment of your codebase, infra, and roadmap — yours even if we don't move forward.

03

Embedded retainer

Weekly cadence, direct async access, deliverables tied to what matters at your stage.

[ 05 — ENGAGEMENT OPTIONS ]

Founding-client pricing — first 3 clients only.

// Advisory
$1,500/mo
8-10 hrs/week

Best for pre-seed, non-technical founders needing a sounding board + architecture sign-off.

// CoreRecommended
$2,500-3,000/mo
15-20 hrs/week

Best for funded startups actively building, hiring, or shipping an AI feature.

30-day paid trial, either side can walk away. Month-to-month after 90 days. Equity optional (0.25-1%, vesting 12-24mo).

[ CONTACT ]

Let's see where your engineering actually stands.

30 minutes. No pitch — just a real look at what's working and what isn't.

Book the call