AI Product Engineer

Magentic
London, United Kingdom
Hybrid

Who this role is best for

Strong fit for AI engineers who build and operationalise agentic systems in procurement, with a focus on Python and LLM deployment.

Best fit for

  • Candidates with experience deploying LLMs in production and managing complex workflows
    — “Have experience shipping LLM-based solutions to production”
  • Individuals who have designed multi-agent systems or frameworks for collaboration
    — “Develop new agentic frameworks to handle multi-agent collaboration”
  • Professionals comfortable with both technical and business stakeholders in enterprise settings
    — “Enjoy communicating with both technical and non-technical stakeholders”

Things to consider

  • The role requires in-office presence for 3 days per week in London.
    — “Hybrid London HQ (3 days per week, with flex if you have appointments etc)”
  • Candidates must demonstrate a track record of delivering high-stakes solutions in procurement.
    — “Procurement is a demanding domain for agents: long-running workflows over messy data, where a wrong answer costs a customer real money”

How to stand out

  • Highlight end-to-end feature ownership and deployment in your resume and interview examples.
    — “Own development and deployment of LLM-based features and agentic workflows end-to-end”
  • Showcase experience in building tools to integrate AI with enterprise systems like ERP.
    — “Operationalise AI features by building tools to connect them to customer systems”
  • Emphasize your ability to benchmark models for performance and safety in high-stakes environments.
    — “Benchmark LLMs across performance, safety and behavioural monitoring”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • owning development and deployment of LLM-based features and agentic workflows
  • developing new agentic frameworks
  • benchmarking LLMs
  • operationalizing AI features
  • collaborating with customers and internal teams
Typical background
engineering experience at tech and product-driven companiesexperience shipping LLM-based solutions to production

Skills & requirements

Required

Llm-based SolutionsAgentic WorkflowsMulti-agent CollaborationBenchmarking LlmsOperationalizing AI FeaturesPythonCommunication SkillsUnderstanding Of Language ModelsComputer Science Fundamentals

Stack & domain

Llm-based SolutionsAgentic WorkflowsMulti-agent CollaborationPerformance BenchmarkingSafety BenchmarkingBehavioral MonitoringAI OperationalizationERP IntegrationCustomer Problem UnderstandingSolution DesignPythonLLM TechnologyComputer Science FundamentalsAgentic SystemsProcurement WorkflowsSupply Chain ResilienceEnterprise ProcurementLanguage ModelsCommunicationTeam CollaborationProblem-solvingAmbiguity NavigationCustomer EngagementTechnical CommunicationMentorshipAILLMProcurementSupply ChainEnterprise Software

About the role

Original posting from Magentic via Ashby

THE ROLE

We're looking for an AI Engineer to build the agentic core of our product. You'll work closely with our CTO and own LLM-based features and agentic workflows end to end, from the agent framework through to the tooling that connects it to a customer's ERP. You’ll ship the cutting edge models and paradigms to Fortune 500 procurement teams.

Procurement is a demanding domain for agents: long-running workflows over messy data, where a wrong answer costs a customer real money. You'll decide how multi-agent collaboration works here, and how we benchmark it for performance, safety and behaviour.

We're building next-generation agentic systems that can manage entire procurement workflows, with a mission to make global manufacturing supply chains more resilient to an ever-changing world. That's a $3tn market opportunity.

We're backed by world-class investors including Sequoia Capital, and you'll be joining a team bringing together experience from OpenAI, Meta, Revolut, NASA and McKinsey.

WHAT YOU’LL DO

  • Own development and deployment of LLM-based features and agentic workflows end-to-end
  • Develop new agentic frameworks to handle multi-agent collaboration.
  • Benchmark LLMs across performance, safety and behavioural monitoring.
  • Operationalise AI features by building tools to connect them to customer systems
  • Collaborate with customers and internal teams to understand customer problems and design optimal solutions

YOU MIGHT BE A GREAT FIT IF YOU

  • Have engineering experience at tech and product-driven companies, so you know what great code looks like
  • Have experience shipping LLM-based solutions to production
  • Have a deep understanding of the core technology behind language models, as well as computer science fundamentals
  • Have built features end-to-end in Python
  • Enjoy communicating with both technical and non-technical stakeholders.

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 £90,000 - £110,000 per annum
  • Enhanced parental leave
  • 25 days holiday exc bank holidays, plus an extra day for our Christmas shutdown
  • In-office lunches provided
  • Salary sacrifice pension and nursery schemes
  • Hybrid London HQ (3 days per week, with flex if you have appointments etc)
  • 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.
  • Skills interview (45 mins): in this step, we'll ask you to prepare a presentation and take Q&A.
  • In-person interview (half-day, paid): for the final step, we invite you to come meet the team in-person. We find this is the best way for candidates to get a sense of what working at Magentic is like. This day will include a culture interview, founder interview and a presentation task / discussion with the team.

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.

Source: Magentic careers (Ashby)

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