Magentic
Back-end Engineer

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The Role
We are looking for brilliant engineers to join our team at Magentic. We’re pushing the boundaries of AI with next-generation agentic systems that can manage entire workflows. We’re focusing on a three trillion dollar market of supply chains and procurement.
Our mission is to make global manufacturing supply chains robust to an ever-changing world, and to harness the potential of generative AI through thoughtful deployment, maximising benefits while prioritising ethical use and safety.
You’ll own full-stack features end-to-end, with a focus on building for enterprise data requirements. You will collaborate closely with customer teams to architect and implement sophisticated data pipelines and APIs, directly fueling our cutting-edge agentic AI with terabytes of real-world supply chain data. You will be instrumental in shaping solutions for enterprise clients, all while learning and growing your AI skills in a truly AI-first company at the forefront of agentic systems.
What You’ll Do
- Design & build scalable, performant backend services and data pipelines written in Python and deployed with Docker & Kubernetes.
- Integrate with enterprise ecosystems - enterprise software systems such as SAP and Oracle ERP, GraphQL/REST APIs, SFTP feeds, and event buses (Kafka, Pulsar).
- Wrangle large, heterogeneous data sets - model, transform, and index multi-modal, multi-terabyte enterprise datasets for advanced workloads.
- Develop enterprise-level next generation AI systems with the support of Magentic’s AI specialists.
- Ship complete customer features - from architecture and code to CI/CD, infra-as-code (Terraform), rollout, and user training.
- Collaborate directly with executives & operators - run white-boarding sessions, turn ambiguous requirements into concrete specs, demo weekly, and iterate fast.
- Champion observability & reliability - instrument services with OpenTelemetry, define SLIs/SLOs, and automate incident response.
- Contribute across the stack - build lightweight front-ends when needed and pair with ML engineers on inference and evaluation pipelines.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
You Might Be a Great Fit if You
- Have 6+ years of professional software-engineering experience.
- Are fluent in Python and comfortable in TypeScript/JavaScript.
- Have built and operated data-intensive systems (batch & streaming) in a cloud environment (AWS, GCP, or Azure).
- Know your way around relational, columnar, and KV/graph databases - and when to use which.
- Have integrated with real-world enterprise stacks - authentication, SSO, legacy ERPs, message queues, ETL tools.
- Can take a loosely defined problem, sketch an architecture, and deliver a production-ready solution in weeks, not months.
- Communicate clearly with both engineers and business stakeholders; you enjoy hopping on a customer call to debug an API contract.
- Thrive in an early-stage, high-ownership environment - prototype today, deploy tomorrow, iterate next week.
Bonus Points
- Experience deploying or consuming LLM-powered services (OpenAI, open-source models, RAG, vector stores) can be a bonus. However, we consider many great candidates without previous AI experience.
- Familiarity with supply-chain, procurement, or manufacturing domains.
Compensation And Benefits
At Magentic, we recognise and reward the talent that drives our success. We offer:
- Competitive Equity: play a real part in Magentic’s upside
- A salary of £125,000 - £140,000 per annum
- Visa sponsorship available
- In-office lunches provided
- Monthly organised socials and an additional flexible monthly social budget for team lunches, coffees, dinners, or activities with colleagues
- Salary sacrifice pension and nursery schemes
- Hybrid London HQ (3-4 days in the office/customer site)
- Annual team retreat—a fully-funded off-site to recharge, bond, and build
Our interview process
We can move quickly through these stages, so let us know if you have any timelines we need to meet.
- Initial call (30 mins): this first step is an opportunity for you to hear more about Magentic and the role, and for us to learn more about how your experience aligns with the role.
- Paired programming interview (45 mins): we'll give you an exercise to demonstrate the key skills for the role.
- In-person interview: for the final step, we invite you to come meet the team in-person and work alongside us! We find this is the best way for candidates to get a sense of what working at Magentic is like. This will include a culture interview, a founder interview and skills-based interview(s) with the team.


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Equal Opportunities and Accommodations Statement
At Magentic, our mission is to build AI that helps solve some of the world's most complex real world problems. We believe building a diverse workforce will be the key to solving this for our customers.
Magentic is committed to creating a truly inclusive team and we’re proud to be an equal-opportunity employer. As we grow, we're intentional about building teams with a broad range of backgrounds, experiences and viewpoints, recognising that this leads to better ideas, stronger collaboration and better outcomes for our customers therefore we strongly encourage applications from all backgrounds and cultures to apply.
We recognise that some groups remain underrepresented within the industry and are committed to creating an environment that celebrates and supports everyone.
Everyone works differently, and we want to ensure our interview process gives you the best chance to show us what you can do. If you require any reasonable adjustments or accommodations, please let us know and we'll work with you to make the process accessible.
Responsible AI Statement
At Magentic, we are committed to developing artificial intelligence that benefits humanity. We push the limits of AI's capabilities and are dedicated to its responsible and safe deployment. Recognising the profound impact of AI, we ensure that its development is centred around human needs and safety, incorporating a wide array of perspectives to fulfil our mission.
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