I'm partnering with a growing technology business looking for a skilled Business Analyst to join their Technology & Data team. This is a role for a true Business Analyst. Someone who enjoys understanding how businesses operate, engaging with stakeholders, mapping complex processes, gathering meaningful requirements and driving measurable improvements across the organisation. You'll act as the link between business and technology, leading discovery, challenging existing processes and ensuring business needs are translated into clear, well-defined requirements that deliver real value. £45,000 - £60,000 London 4 days in the office, 1 day remote No sponsorship available Key Responsibilities: Lead requirements gathering, analysis and documentation Facilitate workshops, discovery sessions and stakeholder meetings Map, analyse and optimise business processes and workflows Translate business needs into clear, actionable requirements Identify opportunities for efficiency, automation and process improvement Produce high-quality BA artefacts including process maps, user stories and business requirements documents Act as the bridge between business and technology teams throughout project delivery What We're Looking For: Proven experience as a Business Analyst within a complex business environment Strong process mapping and business process improvement expertise Excellent stakeholder management and communication skills Experience facilitating workshops and managing requirements across multiple stakeholders Ability to challenge constructively and influence decision-making Consultancy experience would be highly desirable Experience working on technology, digital transformation or data-related initiatives is advantageous There is also a clear progression path into Product Ownership or Product Management for those looking to broaden their career over time. Please send your CV to paul.culmer@xcede.com #BusinessAnalyst #BusinessAnalysis #ProcessImprovement #RequirementsGathering #StakeholderManagement #BusinessTransformation #Consulting #Technology #Data #LondonJobs #Hiring #TechJobs #ChangeManagement #DigitalTransformation

Business Analyst

Product Engineer, Discovery — AI Creator Platform (Remote, CET ±3h)

Via Xcede — confidential search

Fast-growing · real revenue · Gen AI · Remote, CET ±3h overlap · Full-time · Europe-based preferred

The company

One of the fastest-growing products in the AI creator economy. People create AI characters — including verified AI “twins” of themselves — and generate ultra-realistic photos and videos with them. Small, talented team with a Europe-centric core, growing fast on real revenue, evolving from a creation tool into a full content network where creators publish and people discover, follow, and buy.

The role

Own how people find content on the platform: search, ranking, feeds, and following creators. Heavy on systems and backend, with React end to end.

What you’ll own

<ul dir="ltr">
	<li>Search, tags, and ranking
	<li>Personalized feeds that stay fast as the catalog grows
	<li>Following creators and the social graph behind it
	<li>The React side of all of it
</ul>

Your first 8 weeks

<ul dir="ltr">
	<li>You own search or the feed and the team trusts you with it.
	<li>Search results people actually use, with a quality measure the team trusts.
	<li>A ranking or feed change shipped and measured.
</ul>

Who you are

<ul dir="ltr">
	<li>4+ years on backend systems in Go or a similar typed language, with Postgres and production React.
	<li>Search & ranking: relevance, cold start for new content, embeddings — in production.
	<li>Performance: indexes, caching, and data models that stay fast at scale.
	<li>Measurement: you measure quality against outcomes and know which number to trust.
	<li>AI-native: agent tooling every day, held to the same bar as everything else you ship.
	<li>Strong plus: consumer social feeds, recommendation systems, creator platforms.
	<li>Not a fit: frontend-only engineers, or anyone who tunes ranking without measuring it.
</ul>

What you must know

Agents write much of the code here — you’re hired to know when it’s wrong. This gets tested live, with no agent and no framework to lean on: reading a query plan and fixing a slow query, understanding isolation levels and deadlocks; tracing a request end to end and designing retries that stay safe when a timed-out call may have actually succeeded; reading a CPU/memory profile, reasoning about concurrency, adding backpressure before a queue falls over; picking the right data structure for a real task and knowing its costs — including when a simple scan is the right answer.

How they work

Lean on purpose — a handful of people ship what most companies need fifty for. Small teams of 3-4 own an area end to end, no ticket-takers, no waiting on a perfect spec. AI is used daily but never blindly — everything it produces gets reviewed, and when it’s wrong you fix the loop, not just the mistake. Judged on what you’ve built and how fast, not where you worked or how polished you are on a call.

Hiring process

<ol dir="ltr">
	<li>Intro call — 30 minutes, both ways.
	<li>Technical chat — what you built and how.
	<li>Working session — live coding or system design on a real slice, fundamentals without AI.
	<li>Paid 7-day intro — real work together, both sides confirm the fit.
</ol>

Interested? Apply confidentially through Xcede — reach out to Matthew Rees-Davis.

Senior Backend Engineer (Remote EU)

Senior Product Engineer (Full Stack) — AI-Native B2B Trade Platform, Berlin (Hybrid)

Via Xcede — confidential search

The company

A fast-growing, well-funded Berlin-based startup rebuilding B2B procurement from the ground up. This category is a €900B+ market in Europe alone, still run almost entirely by people — four or five intermediaries between supplier and customer, with up to 40% of the margin evaporating along the way. This company is building the alternative: they buy from global suppliers and sell directly to European customers on their own account, running sourcing, pricing, sales, logistics, credit, and financing through AI. One request in, a firm quote back in minutes, delivered on time — no warehouses, no fleet, no inventory risk, every trade pre-sold before it’s bought. They’re also the credit counterparty, scoring and insuring customers in minutes with working capital that’s bank-funded, not equity-funded.

Where they are today: strong triple-digit-million-euro turnover run rate, majority repeat customers, seven live European markets sourcing globally, 80+ people, and a recent well-backed funding round from top-tier European VCs plus bank working-capital facilities.

The role

Much of this company’s trade execution runs through AI agents — and agents are only as good as the product around them: reliable data, well-designed APIs, and interfaces where the team can review, correct, and approve what an agent proposes before real money and real shipments move. As a Senior Product Engineer, you’ll own business problems end to end — talking to the people who use what you build, deciding with Product what to solve, and shipping the whole slice: data model, services, AI agents, and UI. You’ll work in a domain where prices and stock change daily, supplier data arrives in every format imaginable, and a wrong number costs real money.

What you’ll do

<ul dir="ltr">
	<li>Own a business problem from first conversation through production — e.g. making supplier pricing reliable from ingestion all the way to the quote a salesperson sends.
	<li>Build backend services for pricing, inventory, orders, and integrations across suppliers, customers, and logistics partners.
	<li>Build the AI agents themselves plus their tools and APIs, with safeguards — idempotency, validation, audit trails, human review where it matters.
	<li>Design the interfaces where commercial teams review, correct, and approve agent proposals.
	<li>Turn messy external data (price lists, datasheets, stock feeds) into data the business can trust.
	<li>Evaluate and monitor LLM-driven workflows in production.
	<li>Lead technical decisions, document trade-offs, and mentor other engineers.
	<li>Help shape hiring — run interviews, help define what good engineering looks like.
</ul>

Tech stack

Java 21 / Spring Boot 3, Python, LangGraph and LLM APIs (OpenAI, Anthropic, Gemini), PostgreSQL, Kinesis, AWS + Terraform, GitHub Actions, TypeScript / Node.js / Next.js / React. You don’t need all of it on day one — the team leans heavily on AI coding tools and expects you to pick up whatever a given problem needs.

What you bring

<ul dir="ltr">
	<li>5+ years building and running production software with real users and real consequences.
	<li>Strong backend skills at production scale in Java or a comparable language (Kotlin, C#, Go) — willingness to work in Java/Spring Boot specifically.
	<li>Experience designing distributed, event-driven systems with a focus on data correctness and failure modes.
	<li>Solid PostgreSQL and hands-on AWS experience.
	<li>Full-stack delivery capability — your depth is backend, but you can ship a good interface in TypeScript/React when the problem needs it.
	<li>Strong product sense — you ask why before how, talk to users, and turn vague problems into clear plans.
	<li>Comfort in a fast-growing, fast-changing environment.
	<li>A track record of solving business problems, not just technical ones.
	<li>Curiosity and good engineering judgment about LLMs/agents is a must; hands-on experience building with them is a strong plus.
	<li>Bonus: experience in trading, marketplaces, supply chain, fintech, or another domain where data errors cost real money.
</ul>

Practical details

Berlin, hybrid. English-speaking environment. Learning/development budget included.

Interested? Apply confidentially through Xcede — reach out to Matthew Rees-Davis.

Senior Product Engineer (Backend Leaning)

VP Engineering — AI-Native B2B Trade Platform, Berlin

Via Xcede — confidential search

The company

A fast-growing, well-funded Berlin-based startup rebuilding B2B procurement from the ground up. This category is a €900B+ market in Europe alone, still run almost entirely by people — four or five intermediaries between supplier and customer, with up to 40% of the margin evaporating along the way. This company is building the alternative: they buy from global suppliers and sell directly to European customers on their own account, running sourcing, pricing, sales, logistics, credit, and financing through AI. One request in, a firm quote back in minutes, delivered on time — no warehouses, no fleet, no inventory risk, every trade pre-sold before it’s bought. They’re also the credit counterparty, scoring and insuring customers in minutes with working capital that’s bank-funded, not equity-funded.

Where they are today: strong triple-digit-million-euro turnover run rate, majority repeat customers, seven live European markets sourcing globally, 80+ people, and a recent well-backed funding round from top-tier European VCs plus bank working-capital facilities.

The role

As VP Engineering, you own the Engineering organization and turn the platform and AI vision into shipped systems. You report to the CPO and partner closely with product, commercial, operations, and finance — leading Senior Product Engineers, Staff Engineers, and QA. This is an execution mandate, not a caretaking one: you carve the core systems into a modern platform, build the AI agents into one holistic system running the trade lifecycle end-to-end, and scale the team that delivers it. You inherit a working machine at full speed — the job is to rebuild it in flight without losing a day of momentum. Year-one priorities: carving out the transaction core and bringing the AI agents into one orchestrating layer.

What you’ll do

AI & Automation

<ul dir="ltr">
	<li>Build the AI agents into one holistic, orchestrating layer across sourcing, pricing, quoting, sales, logistics, and financing.
	<li>Drive full transaction-lifecycle automation; own automation-rate and no-touch-quote targets as first-class delivery KPIs.
	<li>Work with the data team (sits with the CPO) on making every transaction make the system smarter.
	<li>Stay at the practical frontier of agentic AI — ship what creates leverage now, skip the demo-ware.
	<li>Put guardrails, evals, and human-in-the-loop controls in place wherever automation touches money or customers.
</ul>

Platform & Architecture

<ul dir="ltr">
	<li>Own execution of the target architecture — the system of record for the company’s trade platform.
	<li>Lead the carve-out of the transaction core into a modern, modular light ERP, with a clear migration path and zero disruption to daily trading.
	<li>Shape the role of Salesforce in the landscape — what stays, what moves to the new core, how the two work together.
	<li>Make pragmatic build-vs-buy calls and keep technology cost per transaction on a falling curve.
	<li>Make new-market launch a repeatable platform motion — geographies, currencies, languages, compliance, built in rather than bolted on.
	<li>Keep the platform ready for technical due diligence at any moment.
</ul>

Engineering Organization & Talent

<ul dir="ltr">
	<li>Lead the engineering org: onsite talent in Berlin plus a nearshoring team you manage directly, not at arm’s length through a vendor.
	<li>Build lean by default — raise output through AI across the engineering workflow rather than growing headcount. Lead as an AI-first engineering leader.
	<li>Hire and develop senior engineering leaders, including 1-2 Staff Engineers reporting to you who own architecture across teams.
	<li>Build a culture of ownership, speed, and craftsmanship — small teams, high leverage, no bureaucracy.
	<li>Stay hands-on: review designs with your Staff Engineers, pair on the hardest problems, keep decisions close to the code.
</ul>

Enablement & Data Integrity

<ul dir="ltr">
	<li>Enable business teams to build and automate with AI safely — paved paths, standards, and review practices for non-engineers.
	<li>Partner with the CPO on data integrity — one source of truth, clear access and quality controls.
	<li>Make speed and safety one operating model, not a trade-off, and communicate that clearly across the company.
</ul>

Delivery & Cross-Functional Partnership

<ul dir="ltr">
	<li>Act as technical sparring partner to the CPO on architecture, roadmap feasibility, and sequencing.
	<li>Translate the product roadmap into shipped software; turn commercial/operations needs into delivery.
	<li>Support the CPO and CEO in technical due diligence with a clear, numbers-backed view of architecture, data, and AI.
</ul>

What success looks like

Engineering operates with clear ownership and no loss of delivery speed. The transaction core runs on a modern, modular platform — carve-out live, migration 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, one bar across interviewers.

What you bring

<ul dir="ltr">
	<li>Senior engineering leadership at scale — run and grown multi-team organizations, ideally across more than one location.
	<li>Deep experience with transactional platforms, ERP-style systems, or comparable systems of record — ideally including regulated financial flows (payments, lending, KYC) and re-platforming/carve-outs in a live environment.
	<li>Hands-on track record shipping AI/ML in production, with real judgment on where agentic AI creates leverage today.
	<li>A demonstrated AI-first, lean mindset — you’ve actually used AI in your own org to raise output without growing headcount, not just talked about it.
	<li>Strong architectural judgment, with security and data protection built into your decisions, and enough technical depth to stay close to the code.
	<li>Judgment on where reliability must be absolute vs. where speed wins — fast on everything reversible, a high correctness bar on irreversible, money-touching paths.
	<li>Plus: enabling non-engineering teams to build safely with AI, with the communication skills to carry that across a company.
	<li>Plus: comfort in a company where operations come first and software follows.
	<li>A commercial mindset — engineering decisions anchored in unit economics, working capital, and speed for buyers and suppliers.
	<li>Plus: experience with Salesforce as part of a larger system landscape.
</ul>

Practical details

Location: Berlin. Process: conversations with the CPO, the CEO, Chief of Staff, and members of the engineering team.

Interested? Apply confidentially through Xcede — reach out to Matthew Rees-Davis.

VP Engineering (hands-on)

Matthew has specialised in the Tech and Data market since 2014, navigating key industry shifts from the rise of DevOps and Data Science to today’s AI boom. Focused on the Berlin and Hamburg markets, he has supported businesses at every stage of growth, from building founding teams to delivering strategic leadership hires. He is also active in the local tech community, hosting leadership dinners and TA brunches to connect and share insights.

Senior Backend Engineer (Remote EU)

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Matthew Rees-Davis

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