{"id":1485869,"url":"https://alion.io/job/kernel-ai-ops-engineer-product","title":"AI Ops Engineer (Product)","company":{"id":456080,"name":"Kernel","domain":"kernel.ai","url":"https://alion.io/company/kernel-9","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","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":60000,"max":85000,"currency":"GBP","period":"year","gross":null,"usd_annual":112449},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AIOps","optional":false},{"name":"Canva","optional":false},{"name":"LLM","optional":false},{"name":"Mistral","optional":false},{"name":"OpenAI","optional":false},{"name":"Slack","optional":false}],"status":"live","first_seen_at":"2026-09-29T21:38:23Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-01T10:44:43Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About Kernel\nAgents are starting to sell, buy and operate on behalf of companies. But before an agent can close a deal, qualify an account, route a lead or assess risk, it has to answer a basic question: which company is this?\nToday, that answer is messy, and no one answers it reliably. Business identity lives across CRMs, ERPs and third-party datasets full of duplicates, missing parent companies, stale addresses and incorrect enrichment. The cost shows up across the enterprise: sales teams miss revenue opportunities because they lack the right account context; operations teams take on avoidable exposure because risk signals are fragmented or wrong; and finance teams end up chasing and writing off bad debt that should have been caught earlier.\nHumans have worked around that mess for years. Agents cannot. They need a reliable business identity layer they can trust.\nKernel is building that layer: the business registry for agents. We issue a permanent KERN ID for every business, plus the context an agent needs to act on it. Ops, data and revenue teams at Gong, Legora, Mistral, Canva and Checkout already use Kernel on their own systems. Agents are next, and there will be far more of them.\nWe have raised $14M from top VCs and operators at Plaid, OpenAI, Slack and others, and we are growing 5x YoY.\nThe Role\nWe’re looking for an AI Ops Engineer for our product team to build the internal systems that help Kernel scale without adding unnecessary manual work.\nYou’ll work across Product, Customer Support, and Engineering - finding the highest-leverage problems and building practical AI-powered workflows.\nThis is a hands-on builder role. You’ll take ideas from a vague business problem to a tool or workflow that people use, then maintain and improve it in production. You’ll choose the fastest sensible approach for each problem - coding agents, automation platforms, APIs, data pipelines or lightweight code.\nYour focus area will be whatever is the most critical blocker for Kernel’s growth, whether that’s automating our customer support, tying our data feedback loop to automatically seed our evals (benchmarks), building tooling for our sales team to demonstrate Kernel, and so on.\nYou’ll report to Marcus Henglein, our co-founder who leads our Product, Engineering, and Client Delivery teams.\nWhat You’ll Be Doing\nAutomating customer support: The first focus area is to lead our initiative on automating as much of our technical customer support as possible, leveraging Kernel’s docs and MCPs, the right kind of AI tooling, and working closely with the engineering team.\n\nTurning user feedback into evals: Build workflows that turn data issues reported by users into test cases, helping Kernel catch recurring errors and measure improvements.\n\nKeeping docs current: Build workflows that detect product changes and keep our documentation accurate.\n\nMaking Kernel easier to demo: Build tools that help our sales team prepare and run demos using relevant account data.\n\nPriorities shift, problems often start loosely scoped, and you’ll own the work through maintenance.\nWhat You Bring\nA track record of shipping: you’ve built tools, automations or AI workflows that people use every day, ideally inside a small, fast-moving startup. Around 2-5 years of experience is typical, but what you’ve built matters more than your years. Ex-founders welcome\n\nCurious about product: you’re keen to learn how a product/engineering organization works in a fast-paced startup environment\n\nAI-tool obsessed: you are constantly testing new models, agents, MCPs and workflows, and you have the judgement to turn them into reliable systems that people actually adopt - but without turning off the “Local LLM” that you were born with (your brain)\n\nStrong data instincts: you can turn fragmented, messy information into reliable workflows and create feedback loops that keep it trustworthy\n\nCan’t unsee inefficiency: you see the company as a connected system; when you find a broken or unnecessarily manual process, your instinct is to understand it, build the fix and make sure it sticks\n\nArtisanal programming experience is not required for this role, and you don’t need a traditional software engineering background.\nThis role may not be for you if you:\nPrefer deep specialization over breadth: this role means switching between projects and teams, depending on business needs\n\nPrefer steady-state work over project-based sprints: priorities will shift as the business evolves\n\nOnly want “strategic” work: you will personally build the tools, clean the data and fix the workflows\n\nNeed every task to be clearly scoped before starting: ambiguity and learning on the fly are constant\n\nAvoid operational grunt work or lose interest after the prototype\n\nWant to work in a more structured 9-to-6 environment or in a remote/hybrid setup: we are in the office together 4-5 days a week and the pace is high\n\nWhat We Offer\nWe will do our best to offer you a ride of a lifetime. It will not be easy, but it will be thrilling.\nSalary: £60,000-£85,000 + equity\n\n24 days holiday per year + bank holidays\n\n£450 monthly office dinner allowance\n\n2 weeks work-from-anywhere\n\nGenerous parental leave policy\n\nPension plan\n\nTop-spec equipment and central London office\n\nTeam events and dinners\n\nWork directly with the founders to deploy AI across a fast-growing company\n\nHigh-autonomy, high-trust environment with a small team shipping at pace\n\nInterview Process\nStage 1 - Video call with the Hiring Manager.\nStage 2 - Case study interview (in person) with the team.\nStage 3 - Values interview with the Founders.\nIf there is mutual fit, we move to references and offer.","description_format":"text","description_chars":5651,"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","Parental leave"],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Data Quality & Observability","B2B Company & Contact Data"],"lifecycle":[{"event":"open","at":"2026-09-29T23:14:40Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":15,"reasons":["conf:4","velocity","win:early","comp:junior"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":112449,"is_top_pay":false},"html_url":"https://alion.io/job/kernel-ai-ops-engineer-product","json_url":"https://alion.io/job/kernel-ai-ops-engineer-product.json","meta":{"generated_at":"2026-10-01T13:01:04Z","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":4533,"day_limit":5000,"remaining_today":467,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}