{"id":816188,"url":"https://alion.io/job/magentic-forward-deployed-engineer","title":"Forward Deployed 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":"Solutions","role_family":"Solutions","seniority":"junior","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":50000,"max":65000,"currency":"GBP","period":"year","gross":null,"usd_annual":86105},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-04-02T15:01:19Z","employer_posted_date":"2026-04-02","last_verified_at":"2026-10-01T23:15:45Z","board_verified":true,"closed_at":null,"days_open":182,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":181},"description":"Backed by global technology visionaries like Sequoia Capital, Magentic brings together world-class AI engineering (formers from OpenAI, Meta, and AWS) with procurement expertise (formers from McKinsey & Company and ABInBev).\nWe are looking for brilliant Forward Deployed 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 the $3tn market of supply chains and procurement.\nOur 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.\nForward-Deployed Engineers sit at the intersection of product, engineering, and customer success. You will collaborate closely with customer teams to understand their problems and data, enabling our product engineers to build impactful features. You will be instrumental in shaping solutions and recommending new features for enterprise clients, all while learning and growing your AI skills in a truly AI-first company at the forefront of agentic systems.\nWhat You’ll Do\nYou’ll have a huge impact on both Magentic’s commercial success and our product direction. This is a rare opportunity to help build a rocket ship. As we grow, you could develop into product management or engineering, into a leader in our customer engineering space, even into sales, as you discover your strengths and interests.\nBuild strong relationships with our flagship clients -household names in the enterprise manufacturing space.\n\nAnalyse large, unstructured data sets -dig around to discover value that our customers are missing and help configure our product to surface that value.\n\nCollaborate directly with executives and operators -run white boarding sessions, turn ambiguous requirements into concrete specs, demo our product, and train users.\n\nShape our roadmap -gather insights from customers to determine the highest-priority new features and products.\n\nYou Might Be a Great Fit if You\nAre proficient in Python and SQL\n\nHave 2+ years of professional experience\n\nAre a data expert who can extract insights from large, messy data sets with ease\n\nCan take a loosely defined problem, sketch an architecture, and deliver a production-ready solution in weeks, not months\n\nCan communicate clearly with both engineers and business stakeholders\n\nAre keen to travel to spend time with customers on a regular basis\n\nAre an enthusiastic student and user of AI\n\nThrive in an early-stage, high-ownership environment and learn quickly by doing\n\nBonus Points\nFamiliarity with supply-chain, procurement, or manufacturing domains.\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 £50,000-£65,000\n\nHybrid London HQ (4 days in the office/customer site)\n\nLunches provided in our Kings Cross office\n\nMonthly organised socials and an additional flexible monthly social budget for team lunches, coffees, dinners, or activities with colleagues\n\nSalary sacrifice pension and nursery schemes\n\nAnnual team retreat -a fully-funded off-site to recharge, bond, and build.\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.\nOur interview Process\nThere are a quite a few components because it's really important that both we and you have all the information to make a great decision at this stage of our journey. We 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\nTechnical Task (45 mins): this step involves a live coding session with on of our engineers using SQL.\n\nRole-play interview (45 mins): in this step, we present you with a real problem Magentic encounters, and we ask you to design a solution in a whiteboarding exercise.\n\nIn-person interview (1.5 hours): Come see the office, meet the team in-person and do a case-study interview with Robin, our CEO and a culture interview.\n\nResponsible AI Statement\nAt 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":5658,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["AI Agents","Supply Chain AI"],"lifecycle":[{"event":"open","at":"2026-09-12T11:14:23Z"}],"liveness":{"score":4,"band":"cold","label":"Long shot","p_open":1,"p_active":0.142,"p_room":0.28,"age_days":181,"expected_fill_days":30,"reasons":["conf:13","velocity","win:tail","crowd:junior"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":86105,"is_top_pay":false},"html_url":"https://alion.io/job/magentic-forward-deployed-engineer","json_url":"https://alion.io/job/magentic-forward-deployed-engineer.json","meta":{"generated_at":"2026-10-02T03:18:55Z","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":4528,"day_limit":5000,"remaining_today":472,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}