About Andercore
Andercore is the AI-native supplier of industrial materials for energy, infrastructure, and construction in wholesale and beyond.
We trade with global suppliers and distribute to European customers on our own account. Our AI runs the full trade and distribution end-to-end: sourcing, quality, pricing, sales, logistics, and embedded financing. For the customer, it feels like buying from their preferred local supplier; for our partners, it is the most convenient and safe way to do business across borders. Behind it, our software and agentic AI do the heavy lifting that used to take an asset-intensive supply chain with four or five intermediaries and weeks of manual coordination.
Where we are today:
Strong triple-digit-million euro turnover
Seven European markets live
80+ people across Berlin (HQ), offices in London, Mumbai, and Shanghai
$40M Series B just closed, $75M raised to date from Atomico, Project A, and Inven Capital, institutional financing from international banks.
We are building the world's first and last industrial-grade AI operating system for materials, redefining how global trade works in one of the largest and most essential industries on earth.
Role Overview
As VP Engineering, you own the Engineering organization and turn our platform and AI vision into shipped systems. You report to the Chief Product Officer and partner closely with product, commercial, operations, and finance. You lead our Senior Product Engineers, Staff Engineers and QA, and work closely with our product managers, who own product and design.
This is an execution mandate. You carve our core systems into a modern platform, build our AI agents into one holistic system that runs the trade lifecycle end-to-end, and scale the teams that deliver it. You inherit a working machine at full speed: your job is to rebuild it in flight without losing a day of momentum. In your first year, the priorities are the carve-out of our transaction core and bringing our AI agents into one orchestrating layer.
Key Responsibilities
AI and Automation
Build our AI agents into one holistic, orchestrating AI layer across sourcing, pricing, quoting, sales, logistics, and financing.
Drive automation of the full transaction lifecycle, and own automation-rate and no-touch-quote targets as first-class delivery KPIs.
Work with our data team, which sits with the CPO, on systems that make our trade flows a compounding advantage, so every transaction makes the system smarter.
Keep us at the practical frontier of agentic AI: ship what creates leverage now, skip what is demo-ware.
Put the guardrails, evals, and human-in-the-loop controls in place so automation stays reliable where it matters most: money-touching and customer-facing paths, where a wrong output is a real loss, not just a bug.
Platform and Architecture
Own execution of the target architecture for the Andercore platform, the system of record for industrial trade.
Lead the carve-out of our transaction core into a modern, modular light ERP (a lean core system for our trade transactions), with a clear migration path and zero disruption to daily trading.
Shape the role of Salesforce in our landscape: decide what stays on the platform, what moves to the new core, and how the two work together.
Make pragmatic build-vs-buy calls within the platform strategy and keep technology cost per transaction on a falling curve.
Make new-market launch a repeatable platform motion: multiple geographies, currencies, languages, and compliance regimes, built in rather than bolted on.
Keep the platform ready to pass technical due diligence at any moment: architecture, data, and security in shape for the next financing round.
Engineering Organization and Talent
Lead the Engineering organization: onsite talent in Berlin and a nearshoring team. Team structure and ways of working stay in-house, and you manage the nearshoring team directly and actively, not at arm's length through a vendor.
Build lean by default. The goal is not to grow headcount but to build a small, high-leverage team and raise output through AI across the engineering workflow. You lead as an AI-first engineering leader.
Hire and develop senior engineering leaders, including 1–2 Staff Engineers who report to you and own architecture across teams, and raise the talent bar with every hire.
Build an engineering culture of ownership, speed, and craftsmanship: small teams, high leverage, no bureaucracy.
Stay hands-on: review designs with your Staff Engineers, pair on the hardest problems, unblock teams, and keep decisions close to the code.
Enablement and Data Integrity
Enable business teams to build and automate with AI safely. Set the paved paths, standards, and review practices that let non-engineers move fast without compromising quality, security, or the systems underneath.
Partner with the CPO, who owns data, on data integrity: build systems that keep one source of truth with clear access and quality controls, so that faster building never degrades the data the company runs on.
Make speed and safety one operating model, not a trade-off, and communicate it across the company so every team knows how to move quickly within clear boundaries.
Delivery and Cross-Functional Partnership
Act as technical sparring partner to the CPO on architecture, roadmap feasibility, and sequencing.
Translate the product roadmap into shipped software, and turn front-line needs from commercial and operations into delivery.
Support the CPO and CEO in technical due diligence with a clear, numbers-backed view of architecture, data, and AI.
Communicate technical priorities and trade-offs transparently across the company, so everyone understands what we build and why.
What Success Looks Like
Engineering operates with clear ownership and no loss of delivery speed.
Our transaction core runs on a modern, modular platform: the carve-out is live and the migration path is executed.
One orchestrating AI system increases automation rate and transactions per employee, quarter over quarter.
Technology cost per transaction falls while volume grows.
Architecture, systems, and AI stand up to any technical due diligence.
Hiring runs fast and consistently: senior hires close within six weeks, with one bar across interviewers.
What You Bring
Senior engineering leadership at scale, having run and grown multi-team organizations, ideally across more than one location.
Deep experience with transactional platforms, ERP-style systems, or comparable systems of record, ideally including regulated financial flows such as payments, lending, or KYC, and re-platforming or carve-outs in a live environment.
Hands-on track record shipping AI or ML in production, with a real sense for where agentic AI creates leverage today.
A demonstrated AI-first, lean mindset: you have applied AI in your own engineering organization to raise output without growing headcount, not just talked about it.
Strong architectural judgment, with security and data protection built into your decisions, and enough technical depth to stay close to the code.
The judgment to know where reliability must be absolute and where speed wins: you move fast on everything reversible and hold a high correctness bar on the irreversible, money-touching paths.
A plus: a track record of enabling non-engineering teams to build safely with AI, balancing speed
against quality and data integrity, and the communication skills to carry that across a whole company.
A plus: comfort in a company where operations come first and software follows, turning manual services into products.
A commercial mindset: you anchor engineering decisions in unit economics, working capital, and speed for buyers and suppliers.
A plus: experience with Salesforce as part of a larger system landscape.
Practical details
Location: Berlin
Process: conversations with the CPO, the CEO, Chief of Staff, and members of the engineering team.
We are an equal-opportunity employer and welcome applicants from all backgrounds, regardless of race, ethnicity, gender identity or expression, sexual orientation, religion, age, disability, or any other characteristic. We believe that diversity drives innovation, creativity, and collective strength.