AI Engineer at TechTruth.ai

Why Commit; Amsterdam; Hybrid; EUR 45,000 - 65,000; Full time

Benefits offered by this job

Base at The Stack, Amsterdam

Flexible hours

Hands-on ML production

Job summary

Why Commit is seeking a junior engineer to help move the Ghost Code Scanner from beta into production, building evaluation flows and scoring models using Python.

You will run pitch decks through the system, iterating on benchmarks by sector, and collaborate with senior engineers to ensure reliability and scalability.

Your base is Amsterdam at The Stack; flexible hours and both part-time or full-time options, joining a team blending AI with venture dealflow.

Qualifications

• You are comfortable in Python and Git, and understand CI/CD and ML deployment.
• Experience with LLM APIs, prompting, and evaluation is a plus.
• A degree in AI/ML, data science or CS is not strictly required.

Responsibilities

• Build evaluation flows, scoring models, and production-ready tooling.
• Validate with real pitch decks and benchmark by sector.
• Work with engineers and founders to ship features and improve the product.

Skills

Python

Git

CI/CD

MLOps

LLM APIs

Prompting

Production deployment

Education

Degree in AI/ML, data science or CS

Job description

Most pitch decks mention AI, and TechTruth helps investors see how much of that is real for a specific company.For each deck, the system runs hundreds of background checks, benchmarks the result against the 1,300 decksalready in the system, and folds in feedback from founders and investors who disagreed with our score. Whatcomes out is a score an investor can actually argue with.

Five months in beta brought real traction and learnings. Funds, founders and incubators across Benelux and DACHalready use it, and we are looking for a junior engineer to help take it beyond beta, with experienced colleaguesaround you.

We measure claims against evidence. Here are ours.

Claim People actually use this

Evidence 1,300 decks fully AI-analysed, across 12 industries

Claim Funds build it with us

Evidence 20 VC & PE funds shaping the scoring model directly

Claim Founders are in the loop

Evidence 400 founders feeding back on what the model got wrong

• Better scoring. Investors already use the score and it lands. The work is sharper precision andfeedback loops robust enough to improve without breaking what works.
• Sharper benchmarks. 1,300 decks give us a strong base. The gap is stage and sector nuance: adeep-tech seed deck should not be judged like a B2B SaaS Series A.
• More sectors. Twelve industries already, and the score holds. Each new sector needs its ownreference points so quality stays there as we expand.
• A self-service portal, so a fund can run a deck without us in the loop.
• Rollout to more funds and incubators, which changes what the product has to handle.
• Higher quality throughout: fewer false flags, clearer reasoning, faster turnaround.

What you will do

• Build. You improve the product: evaluation flows, scoring models, and the Ghost Code Scannerwe ship with Enjins (GitHub checks without sharing private code). You write Python that others have to read,work in Git, and get things into production rather than leaving them in a notebook. There is room toexperiment with modern LLM tooling, but what ships has to keep running.
• Validate. You run real pitch decks through the system, note where it fails, and help buildbenchmarks per sector and stage, comparing scores to what experienced reviewers think.
• Work the dealflow. You look at incoming companies with us: does the technology hold up, and doesthe claim match what is actually built? You form a view and you say it out loud, with senior people in the roomto argue back. Demo days and investor sessions are part of it, and what you hear there goes straight back intothe product.

Who we are looking for

What matters You like building with code and AI tools, and side projects, scripts or small experiments tell us morethan a polished CV.

What you can already do You are comfortable in Python, use Git without thinking about it, and understand enough about how softwareis tested and deployed that CI/CD and basic MLOps are familiar terms. You have worked with LLM APIs,prompting and evaluation, and you have shipped something worth showing, whether that is a course project,a side repo or a hackathon demo. We would rather see running code than a perfect plan.

What you will pick up here You will learn how to get ML into production properly: pipelines, monitoring, evaluation you can trust,and working in the cloud. You pick this up alongside Enjins engineers who do it for a living, and nobodyexpects you to arrive with all of it.

About diplomas A degree in AI/ML, data science or CS is one route here. It is not the only one and it is not required. Wecare about what you have made.

Uncertainty Where this product goes in two years is not decided, and neither is where this market goes. If you need afixed roadmap to feel safe, this will not suit you. If the open end is what interests you, we should talk.

How you work You sit in rooms with founders and investors and ask when something does not add up. Curiosity is central. Ifyou would rather take something apart than wait for someone to file a ticket, you will fit.

What you get

• Real users and real data from day one, not a sandbox or a made-up brief.
• Production engineering learned next to Enjins engineers who do it for a living, and a live fund at Volve tosee the work land in.
• Regular contact with the funds, founders and incubators who already use the product across Benelux and DACH.You meet companies before the market does.
• Room to co-invest alongside Why Commit on deals you helped look at. Same terms as us, no minimum tickettheatre.
• Hours that fit around you, part-time or full-time, and a base at The Stack in Amsterdam.

Your base is Amsterdam. Expect roughly one or two days a week elsewhere, and expect that mix to shift asthe work does.

Amsterdam The Stack

Your home base, opening September 2026 as a workspace for AI builders with 4,500 m² and 200+ founders planned by 2029. Co-founded by Maarten Stolk (Deeploy, Enjins).

Where most of the engineering happens and where the experienced engineers sit.

Berlin Merantix AI Campus

Enjins' German base and one of Europe's densest AI clusters. Visits are occasional, not weekly.

Do not send a CV.

Send us your work: a repo, something you deployed, or an experiment that failed in an interesting way. Tell uswhat you built, what you learned, and how many hours a week you have.

We read everything and reply within a week. First conversation is a call with Bastiaan, second is a workingsession on something real, not a take-home assignment invented for the occasion.