AI-native engineering.

Fractional CTO for founders and technology leaders across AU / APAC.

When delivery has broken down, I fix it. When teams want to move to AI-native delivery properly (not just adopt the tools), I build the infrastructure. Either way, I leave your team in better shape than I found it.

AI-native delivery in practice

Review pull request #849 — atlas-platform
/reviewhttps://github.com/atlas-platform/pull/849
Thought for 1s
Code Review — PR #849

Fetching the diff to classify the tier.

Trusted by

HarvestStack
Mist
PayChoice
Balmer Agency
10x Banking
KPMG
JP Morgan
Deutsche Bank
Morgan Stanley
Citi
Credit Suisse
Merrill Lynch
CBA
NAB
Westpac
Prudential
London Stock Exchange
Lloyds Bank
HarvestStack
Mist
PayChoice
Balmer Agency
10x Banking
KPMG
JP Morgan
Deutsche Bank
Morgan Stanley
Citi
Credit Suisse
Merrill Lynch
CBA
NAB
Westpac
Prudential
London Stock Exchange
Lloyds Bank

When does a fractional CTO make sense?

Your platform has been in build for months and hasn't shipped. You suspect the problem isn't the team, but you're not sure what it is.

Your architecture made sense at MVP. Now it's slowing everything down, and you're not sure whether to fix it or start over.

You're heading into a raise and your technical story needs to be airtight. You can't afford for diligence to surface things you didn't know about.

Something went wrong. Security incident, data issue, compliance gap. You need someone who's been here before.

You need senior technical leadership and hands-on capability, but a full-time CTO isn't the right move yet.

Your team has adopted AI coding tools but delivery hasn't actually changed. Code ships faster but review is getting skipped, security gaps are widening, and nobody's sure what the AI actually wrote.

Thread in #founders

What I find when I look

Technical Assessment — Vela

Code, infrastructure, product, team & compliance · May 2026

13 areas assessed

150+ findings

3 Critical
6 High
4 Medium
CriticalDatabase security
CriticalTest coverage
CriticalInfrastructure
HighFeature completeness
HighSecurity integration
HighTeam & knowledge risk
HighPayment processing
HighEngineering documentation
HighDependency vulnerabilities
MediumCost at scale
MediumCompliance endpoints
MediumPrivacy enforcement
MediumRegulatory readiness
Not production-readySignificant gap between designed and integrated protections

Engagements take different shapes.

AI-speed engineering, without losing control.

"A team of three with this infrastructure ships with the coverage and governance of a team of fifteen."

Three engineers. 300% more customers. 500% more suppliers. No additional headcount.

Most teams use AI to make coding faster. I use AI to make the whole delivery system faster, without weakening the controls.

Pull requests11
7 Open·1,247 Closed
LabelReviewsSort
feat(HAR-1247): order consolidation for multi-supplier deliveriesauto-merge-eligible
#1247·opened just now· 3
feat(HAR-1246): bulk invoice export with configurable date rangesneeds-review
#1246·opened 12s ago· 14
fix(HAR-1245): correct pagination offset on order history viewauto-merge-eligible
#1245·opened 34s ago· 1
feat(HAR-1244): multi-currency pricing for international suppliersneeds-review
#1244·opened 1m ago· 27
chore(deps): bump @testing-library/react from 14.2 to 15.0auto-merge-eligible
#1243·opened 2m ago· 2
feat(HAR-1242): weekly delivery digest email for buyersneeds-review
#1242·opened 3m ago· 8
fix(HAR-1241): resolve race condition in checkout on low stockauto-merge-eligible
#1241·opened 4m ago· 5

Ships faster

A one-line fix clears in minutes. A new authentication flow gets specialist review before it merges. Review agents catch problems before a human sees the code. High-risk changes get more scrutiny, not more waiting. Low-risk changes get pattern-matched and move straight through.

Never blocked by security

Continuous scanning with findings routed directly to your issue tracker, not a quarterly report. Findings get smarter as your codebase evolves. Security runs in parallel with delivery, not instead of it.

Scales without headcount

Release notes, CI guardrails, and convention specs run automatically. Your team focuses on building. Three engineers deliver like ten. The infrastructure outlasts the engagement. Your team runs it themselves.

Automated security review
Web · Mobile · API · Cloud · Infra
34 agents · 4 tracks
Queued3
SEC-44

API rate limiting & abuse prevention

APIcritical
api-security-agent
SEC-43

Third-party dependency vulnerabilities

Infra
dependency-scanner
SEC-42

Mobile data storage & encryption

Mobile
mobile-security-agent
In Progress3
SEC-4111/14

Authentication & session management

APIcritical
api-security-agent
SEC-406/9

Cloud storage permissions audit

Cloudcritical
cloud-security-agent
SEC-395/5

Browser security headers & CSP

Web
web-security-agent
In Review2
SEC-385/5

Secrets & credential management

Infra
secrets-scanner
SEC-3712/12

User data exposure on endpoints

APIcritical
api-security-agent
Done3
SEC-36

Network access control policies

Cloud
cloud-security-agent
SEC-35

Frontend authentication flows

Web
web-security-agent
SEC-34

Infrastructure access & IAM review

Infracritical
infra-security-agent

In practice

A production bug affecting 40% of users. Under one hour from identified to merge-ready.

Validated finding, Linear ticket, fix with tests, architecture review, CodeRabbit iteration, full E2E and API suite, Playwright, deterministic checks, PR raised. No controls bypassed. The point is not that AI wrote the fix quickly. The point is that the whole delivery control loop ran at AI speed.

fix(HAR-1247): app visibility broken for subset of users on shared accountsReady to merge
auto-merge-eligible
All checks have passed · 4 skipped, 9 successful
Branch Name / check-branch-namein 2s
Security Scan / CodeQLin 52s
CodeRabbit / code-reviewin 3m
Architecture Review / arch-reviewin 6m
E2E API Tests / api-suitein 3m 12s
Playwright E2E · shard 1/4in 4m 08s
Playwright E2E · shard 2/4in 3m 55s
Playwright E2E · shard 3/4in 4m 21s
Playwright E2E · shard 4/4in 3m 47s
Merge pull request

Outcomes

A fintech startup with no tech team and one week before an investor presentation. Full technical audit and investor-ready narrative built from scratch. Investment secured.

A farm-to-plate platform with no product and no team. MVP built and funded. AI delivery infrastructure installed. Now serving 300% more customers with 500% more suppliers, without adding headcount.

A SaaS platform three years into a migration that wasn't moving. Unblocked and delivered. Engineering manager emerged CTO-ready. Engagement closed because there was nothing left to fix.

A $60M Banking-as-a-Service implementation. Core banking, payments (BPAY, NPP, Direct Entry), electronic KYC. A team of 20 mobilised in 12 weeks and a live platform at the end of it.

A global SaaS platform rebuilt across five countries. ISO 27001 and GDPR-aligned architecture. A Royal Commission data ingestion system processing over 100,000 customer records.

Two pre-launch startups, two audits, 150+ findings across product, DevOps, security, and code. The developers weren't delivering what they'd been paid for. Honest diagnosis, a clean exit, and a referral to a team that could actually ship.

What clients say.

"Shariq genuinely thinks in terms of business cost and outcomes and not just engineering. Every decision is made with delivery efficiency in mind. That mindset is vanishingly rare."

Sascha Rust
Sascha Rust
Co-Founder & Director, HarvestStack

"We'd been stuck on the same migration for three years. Shariq got it moving, grew the engineering manager into a leader, and handed off to a permanent CTO. Clean exit."

Tanith Buda
Tanith Buda
CEO, PayChoice

About Shariq

Shariq Khwaja

I've been building and fixing software systems for 25 years. Starting on Unix, C, and shell scripts, working through trading systems, core banking, enterprise SaaS, and now startup and scaleup technology.

The thread through all of it: I'm most useful when the stakes are high and the situation is messy. Stalled delivery, fragile architecture, teams that need restructuring, platforms that should have launched months ago. That's where I do my best work.

Over the last three years, that's become the core of what I do: coming in when things are broken, finding what's actually wrong, fixing it, and leaving behind something better than I found.

The current version of "better than I found" involves AI delivery infrastructure. I build systems that automate the costly, error-prone parts of engineering (code review, security scanning, architecture governance, release management) so smaller teams can ship with the rigour of much larger ones.

Based in Melbourne. Working across AU and APAC.

Rates are transparent: $2,500/day, or from $16,000/month for an ongoing engagement.

If that sounds like what you need, let's talk.

Let's talk.

We talk for 30 minutes. No pitch. If there's a fit, I'll tell you what I'd do.

Currently taking one new engagementAU / APACMelbourne