{"id":913581,"url":"https://alion.io/job/magentic-ai-product-engineer","title":"AI Product Engineer","company":{"id":679690,"name":"Magentic","domain":"magentic.com","url":"https://alion.io/company/magentic","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":3,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-01T05:45:00Z"}},"role":"Product","role_family":"Product","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":90000,"max":110000,"currency":"GBP","period":"year","gross":null,"usd_annual":145716},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"LLM","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-09-14T13:13:45Z","employer_posted_date":"2026-09-14","last_verified_at":"2026-10-01T06:04:13Z","board_verified":true,"closed_at":null,"days_open":16,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":16},"description":"The Role\nWe'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.\nProcurement 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.\nWe'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.\nWe'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.\nWhat You’ll Do\nOwn development and deployment of LLM-based features and agentic workflows end-to-end\n\nDevelop new agentic frameworks to handle multi-agent collaboration.\n\nBenchmark LLMs across performance, safety and behavioural monitoring.\n\nOperationalise AI features by building tools to connect them to customer systems\n\nCollaborate with customers and internal teams to understand customer problems and design optimal solutions\n\nYou Might Be a Great Fit if You\nHave engineering experience at tech and product-driven companies, so you know what great code looks like\n\nHave experience shipping LLM-based solutions to production\n\nHave a deep understanding of the core technology behind language models, as well as computer science fundamentals\n\nHave built features end-to-end in Python\n\nEnjoy communicating with both technical and non-technical stakeholders.\n\nCompensation and Benefits\nAt Magentic, we recognise and reward the talent that drives our success. We offer:\nCompetitive Equity: play a real part in Magentic’s upside\n\nA salary of £90,000 - £110,000 per annum\n\nEnhanced parental leave\n\n25 days holiday exc bank holidays, plus an extra day for our Christmas shutdown\n\nIn-office lunches provided\n\nSalary sacrifice pension and nursery schemes\n\nHybrid London HQ (3 days per week, with flex if you have appointments etc)\n\nAnnual team retreat -a fully-funded off-site to recharge, bond, and build\n\nOur Interview Process\nWe can move quickly through these stages, so let us know if you have any timelines we need to meet.\nInitial 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.\n\nSkills interview (45 mins): in this step, we'll ask you to prepare a presentation and take Q&A.\n\nIn-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.\n\nEqual Opportunities and Accommodations Statement\nAt 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.\nMagentic 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.\nWe recognise that some groups remain underrepresented within the industry and are committed to creating an environment that celebrates and supports everyone.\nEveryone 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.\nResponsible AI Statement\n 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.","description_format":"text","description_chars":4600,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Parental leave"],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["AI Agents","Supply Chain AI"],"lifecycle":[{"event":"open","at":"2026-09-14T18:10:30Z"}],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.701,"p_room":0.9,"age_days":16,"expected_fill_days":36,"reasons":["conf:13","velocity","win:mid"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":145716,"is_top_pay":false},"html_url":"https://alion.io/job/magentic-ai-product-engineer","json_url":"https://alion.io/job/magentic-ai-product-engineer.json","meta":{"generated_at":"2026-10-01T13:08:28Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4728,"day_limit":5000,"remaining_today":272,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}