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Magentic
AI agents (“Mages”) that run procurement inside large manufacturers
Last verified September 19, 2026 · Updated daily
What Magentic is building
Magentic builds multi-agent systems it calls Mages that work inside a manufacturer's existing software and talk to people the way a colleague would: over Microsoft Teams and email. They cover the procurement loop end to end, from choosing suppliers and negotiating contracts to placing orders and clearing invoices, with human approval kept in the loop for significant decisions. The product is organised around three jobs. Value hunting: spend analysis, category strategy and should-cost analysis across data that lives in ERPs, invoices, emails and spreadsheets. Value protection: watching requisitions in real time, applying compliance rules, routing orders to the right supplier and stopping off-contract purchases. Value recovery: scanning transaction history for price leakage, unclaimed rebates and contract violations. Under it sits a stack the company describes as data ingestion, a harmonised data layer, an agentic engine, procurement-specific knowledge, real-time monitoring and feedback loops, with the model chosen per task rather than one LLM for everything. It is deployed, not demoed. Customers include three of the world's ten largest beverage companies; one processes more than a million orders a year through the platform, another identified $4M in savings, and typical results are 2–5% cost savings with a 60% improvement in data quality. Siemens is the featured customer on the site. The company holds ISO 27001 and SOC 2, which is table stakes for the buyer.
Why this matters
Procurement is the rare agent use case with a number the CFO already tracks: savings. Robin Van Aeken frames the moment as the biggest capex cycle in history, driven by AI demand, colliding with trade disruption and geopolitics; the companies that build intelligence into every decision compound their advantage. The engineering JD puts the market at $3tn. What makes this hard is also what makes it defensible. Odhran O'Donoghue's line is that bringing frontier AI to the physical world means pushing past systems with limited context windows: long-running workflows over gigabytes to terabytes of messy multimodal data, where a wrong answer costs a customer real money. A Series A from Felicis a year after a Sequoia seed, on the back of Global 500 deployments, says the model works in production with the world's least forgiving buyers.
Open roles at Magentic
9 positions we're tracking. Roles are re-checked daily and removed when filled.
AI Product Engineer (£90–110K + equity; owns agentic workflows end to end, works directly with the CTO)
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Watching Magentic
0 applicantsRole spotted & verified
1You get the alert
1You've applied
~8Hits the job boards
250+Hiring outlook
Ten open roles on Ashby (five engineering, four sales and operations, plus an open application), all full-time London hybrid. The CTO's LinkedIn headline literally reads “Hiring!”. The AI Product Engineer posting lists £90,000–110,000 plus equity, three days a week in the London HQ, and a fast three-stage process ending in a paid half-day on site.
Working at Magentic
Magentic is a AI company based in London. Working at a AI company at this stage means opportunity to shape your role based on the company stage.
London is where most Magentic positions are located.
How to actually get hired at Magentic
Why applying the normal way doesn't work
Magentic runs an applicant tracking system, but hiring managers still work referrals first. A cold application to Magentic isn't dead, it's just fourth in line behind internal referrals, sourced candidates and recruiter pipelines.
Who to contact at Magentic
What to show them
A long-horizon agent over ugly procurement data: take a public purchase-order or invoice dataset, dirty it up (duplicate suppliers, inconsistent units, missing contract terms), and build a small multi-agent pipeline that finds off-contract purchases and price leakage with an approval step. Include a benchmark harness that reports precision, cost per run, and a behavioural check (does the agent ever act without approval). Python, shipped.
A cold email that works at Magentic
What Magentic screens for
Felicis leading twelve months after Sequoia seeded the company, with Sequoia and Westly re-upping, is a clean up-round signal. Feyza Haskaraman's thesis is that supply chains are the least glamorous part of the economy and among the most valuable to automate. The hiring plan is visible: five engineering roles including forward-deployed, plus a founding growth marketer and deployment strategists, which is the shape of a company going from a handful of Global 500 accounts to a repeatable motion. The AI Product Engineer role reports into the CTO and owns the agent framework; that seat gets filled once.
Customize your CV for the Magentic role. Matching the job description language helps clear ATS filters.
Don't make these mistakes
Skip consulting-speak about digital transformation and supply-chain resilience. Robin was a McKinsey project leader serving exactly these manufacturers and has heard every version of the deck; he also won Oxford's undergrad innovation prize with a satellite-imagery road-safety model, so he is technical enough to smell a vague pitch. Odhran has an Oxford ML PhD and worked at OpenAI; 'we could put an LLM on procurement' will not land. Their JD names the real problem: long-running workflows over messy ERP data, multi-agent collaboration, and benchmarking agents for performance, safety and behaviour. Talk about that.
Mistakes that kill Magentic applications
Generic CVs stand out at a -person company — and not in a good way. Fastest path to rejection.
Don't open with what you want. Open with what Magentic is dealing with right now — Procurement is the rare agent use case with a number the CFO already tracks: savings, and what you'd do about it.
Most AI applications get ghosted. A day-five follow-up can double your response rate.
Applying to Magentic? Get the contact, not the form.
The Magentic interview process
4 stages · 14 days typical · take-home: yes · modelled from similar companies
We don't yet have verified candidate reports for Magentic. What follows is the typical process for a -person AI company — treat it as a model, not confirmed detail.
Interview stages
Recruiter Screen
Phone or video · 30 min
Basic qualification and logistics
Recruiter or HR
Hiring Manager Interview
Video call · 45 min
Role fit and experience deep-dive
Hiring manager
Technical/Functional Round
Video call · 60 min
Skills assessment and problem-solving
Team members
Final Round
In-person or video · 60 min
Culture fit and cross-functional alignment
Senior leadership
Magentic take-home assignment
Magentic includes a take-home exercise in their interview process. For AI roles, this typically involves a practical problem that takes 2-4 hours. Focus on clean, working code over premature optimization. They're evaluating how you think and communicate, not just the solution.
Magentic interview timeline
Timeline: ~ days. That's about average than the AI median (14 days at people).
Interviewed at Magentic?
Tell us how it went — stages, questions, timeline. Takes 90 seconds and it's how this page stays accurate for the next person.
Submit your Magentic interview experience →Magentic jobs, frequently asked questions
How many jobs does Magentic have open?
As of September 2026, Magentic has 9 open positions.
Does Magentic hire remotely?
Magentic doesn't have remote openings at the moment. All roles are in London.
What roles is Magentic hiring for?
Magentic is hiring across Engineering, Sales, Other, Marketing. The most recent opening is AI Product Engineer (£90–110K + equity; owns agentic workflows end to end, works directly with the CTO).
How do I apply for a job at Magentic?
Use the apply links above, or check our guide to getting hired at Magentic.
Does Magentic respond to cold emails?
Not enough data yet on Magentic's cold email response rates.
Who is the hiring manager at Magentic?
At this size, hiring is usually run by the hiring manager.
How competitive is it to get hired at Magentic?
Expect 100-250 applicants in the first two weeks for AI roles at this size. Apply within 72 hours for best odds.
How many rounds is the Magentic interview?
4 stages: Recruiter Screen, Hiring Manager Interview, Technical/Functional Round, Final Round.
Is the Magentic interview hard?
Expect technical depth and system design, not algorithm trivia. Candidates report Technical Interview as the toughest stage.
Does Magentic give a take-home task?
Yes, Magentic includes a take-home assignment.
How long does Magentic take to get back to you?
Around 14 days across the full process.
What should I prepare for the Magentic interview?
technical depth and system design is the priority. Show you can work autonomously — that matters more than algorithms at people.
Where is Magentic based?
Magentic is headquartered in London, US.
Get Magentic roles before they're posted
A role stays uncontested for about four days. Here's the window — and where we put you in it.
From $5.99/week, cancel any time.
Watching Magentic
0 applicantsRole spotted & verified
1You get the alert
1You've applied
~8Hits the job boards
250+Related
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