§ 01Snapshot
- Level15+ years; founding engineer and CTO of several early-stage startups; applied AI work for well over a decade
- Roles heldCTO of early-stage AI and data startups · CTO of an automated-trading company · technical lead on large-scale public-sector systems · mobile tech lead for a logistics app · founding technical lead taking an idea to an investable company · technical advisor to early-stage founders in an accelerator programme · forward-deployed engineer rolling out AI for sales teams
- Industriescrypto / digital-asset trading, blockchain data, sales technology and AI automation, public sector, B2B logistics, early-stage startups across sectors
- Company typespre-seed and seed startups, accelerator cohorts, small trading operations, B2B AI vendors deploying into customer environments
- SpecialtiesAWS architecture for early-stage products, real-time market-data and execution systems, deploying AI features into customer environments, technical foundations and team setup for a first raise
- Best forsolo founders and pre-seed / seed startups · teams building trading or market-data systems · B2B AI vendors rolling out to enterprise sales teams
- Core stackGo, Python, AWS, real-time data pipelines, APIs and integrations, dashboards, AI-assisted coding tools
- Time zonesEurope
§ 02Services
| ✓ | PR/MR code review | Go, Python |
| ✓ | Architecture review | AWS, real-time pipelines |
| ✓ | Architecture design | MVP foundations, trading and market-data back ends |
| ✓ | Audit / due diligence | pre-raise technical readiness; has helped founders through investor technical due diligence |
| ✓ | Vibe-code rescue | AI-built MVPs heading to AWS |
| ✓ | Team mentoring | founding-team setup, AI-assisted engineering workflow |
§ 03Track record
Automated crypto trading infrastructure
A small trading venture needed to run algorithmic strategies on several crypto networks without manual work. One of our experts built the infrastructure: trading bots, real-time market-data pipelines, strategy back ends, and execution and monitoring on AWS.
Forward-deployed AI rollouts for sales teams
Sales teams wanted AI in their daily workflows, but every customer had different tools and data. Our expert worked inside customer workflows, built prototypes, integrations, automations and dashboards, deployed them into customer environments (APIs, data pipelines, cloud) and debugged production with customer engineers. They fed patterns from the field back into the product.
From idea to an investable technical foundation
A founding team had an idea and needed a product, a technical foundation and an engineering team to raise money. As founding technical lead, our expert set up all three from scratch, and the company reached investment readiness.
Technical advisor to early-stage founders in an accelerator
Early-stage founders in an accelerator programme needed technical judgement before committing to build. Our expert worked with them on validating ideas, setting technical strategy and shaping companies that investors could back.
From pitch deck to an investable data product in months
A data startup had a pitch deck and no product. One of the CTOs in our network built the team and the technical foundation from scratch: a data platform that collects and structures information about crypto projects for other data companies, on Go, Python, AWS and LLM APIs. Within about six months the company raised at a multi-million valuation.
Trading systems where a bug costs real money
Automated trading across several blockchain networks moves real funds, so every failure has a direct cost. One of our experts built and ran these production systems with an explicit failure-first discipline: enumerate the ways each step can fail, fail loudly instead of guessing, and handle each failure mode on purpose.
Technical lead on large-scale public-sector systems
A government organization needed large-scale systems built fast under public pressure and kept stable afterwards. One of our experts led architecture and design on these systems and mentored junior engineers across teams.
Mobile logistics app: fewer crashes, steady releases
A logistics app with thousands of active users was crashing too often for field use. One of our experts led a small mobile team, re-architected the app and cut crashes substantially while keeping a steady release cadence.
Accelerator CTO-in-residence: technical due diligence for founders
Early-stage teams in an accelerator had weeks to validate ideas, build MVPs and convince investors. One of the CTOs in our network advised more than ten of them on technical strategy and MVP scope, helped founders through investors' technical due diligence and helped recruit their first engineers.
§ 04What you can book
AWS architecture review for a seed-stage product
A seed startup runs on AWS that grew by clicking in the console. The expert reviews accounts and environments, IAM, networking, data stores, deployment and cost.
A ranked list of risks (security, cost, reliability) and a target setup the team can move to step by step.
Pre-raise technical readiness review
A founder is about to raise and expects technical questions. The expert reviews architecture, code ownership, cloud setup, security basics and team plan, the way an investor's technical advisor would.
A short readiness memo with gaps to close before the round and answers the founder can give.
Pre-launch review of a trading bot
A team has a profitable back-test and wants to go live. The expert reviews order idempotency, reconnect and gap handling on market-data feeds, position limits and a kill switch outside strategy code, secrets handling, and monitoring.
A go / no-go list with the blocking fixes.
Real-time market-data pipeline design
A team needs live prices from several venues feeding strategies and dashboards. The expert designs ingestion, normalisation, storage and fan-out with explicit handling of gaps, late data and reconnects.
An architecture with failure modes listed and a first working slice on AWS.
Deploying an LLM feature into a customer's sales stack
An AI vendor's pilot works in the demo but stalls inside a customer's CRM and network rules. The expert reviews data access, permissions, integration points and observability, then helps the vendor's engineers ship into the customer's environment.
An integration plan, a deployment checklist and a working pilot.
Production check for an AI-built MVP heading to AWS
A solo founder built an MVP with AI coding tools and wants to put it in front of paying users on AWS. The expert checks secrets, auth, data storage, error handling, deployment and cost.
A fix list ranked by risk, and a minimal, repeatable deployment.
Go and Python PR review for a small team
A small team ships fast with AI-assisted coding and has no senior reviewer. The expert reviews PRs for correctness, concurrency, error handling and cloud cost impact, and leaves notes the team can learn from.
Reviewed PRs plus a short list of team conventions.
Setting up a founding engineering team
A founder needs the first engineers and a way of working. The expert helps define the role profile (stack, cloud skills, comfort with ambiguity and AI-assisted coding), sets up review and deploy habits, and joins early technical interviews.
A hiring profile, an interview loop and a lightweight engineering playbook.