{"id":3519044,"url":"https://alion.io/job/stackgini-product-engineer-mfd","title":"Product Engineer (m/f/d)","company":{"id":688911,"name":"Stackgini","domain":"stackgini.de","url":"https://alion.io/company/stackgini","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Join","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Berlin, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":58000,"max_usd":139000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":14},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Claude","optional":false},{"name":"Cursor","optional":false},{"name":"LLM","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Amazon ECS","optional":true},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"AWS Fargate","optional":true},{"name":"Azure","optional":true},{"name":"GitHub Actions","optional":true},{"name":"Java","optional":true},{"name":"JavaScript","optional":true},{"name":"Kotlin","optional":true},{"name":"Next.js","optional":true},{"name":"OpenAI","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Python","optional":true},{"name":"React.js","optional":true},{"name":"Spring Boot","optional":true},{"name":"Terraform","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-06-11T12:32:30Z","employer_posted_date":"2026-06-11","last_verified_at":"2026-11-03T08:53:43Z","board_verified":true,"closed_at":null,"days_open":145,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":145},"description":"At Stackgini we are building the AI operating system for Autonomous Enterprise IT.\nIT landscapes of large enterprises have never been under more pressure. Thousands of applications to govern. Major transformations to manage. Growing regulatory complexity on one side, business units shipping AI prototypes in days on the other. And in the middle: enterprise IT teams still managing and collecting tech demands manually, managing the complexity of highly integrated processes and systems.\nStackgini changes this fundamentally. Stackgini's system understands its customers' enterprise tech landscape from the ground up, from technical configuration to application documentation, from individual IT demands to dependencies across the entire tech portfolio, with the depth of knowledge of a senior IT expert and the speed of a machine. If you had unlimited budget, you would hire a dedicated IT expert for every IT demand. With Stackgini, this is now possible.\nSome of the largest organizations in this world trust Stackgini including DAX-40 and Fortune-500 customers like Siemens Healthineers or REWE.\nWe're a small, talent-dense team of >10, building what we believe will change how the world's largest companies operate. We are growing fast, and the people joining now are the ones who set the standard - for the product, the culture, and our category. Stackgini will be the place where you will do the most meaningful work of your career.\nTasks\nThe role\nA Product Engineer at Stackgini owns features end to end. You take a customer problem, scope it with Product & CSM, design the solution, build it across the stack, ship it, and stay close to it after release. Recent examples: Product Engineers shipped Decisions and Approvals (a feature for routing IT requests through multi-step approval workflows), built evaluation infrastructure to benchmark agent recommendations against expert baselines, and agentic IT solutions research with our inhouse developed agent tool-use.\nYou are close to users. You join customer calls, run user tests, read support context, and you use that input to decide what should exist and how it should behave. The person building the feature is expected to shape the feature.\nWe have more good ideas than hands. For most reasonable feature ideas the question is not whether we build them, but when. Product Engineers are the people who turn that prioritization into shipped product quickly, without lowering the bar.\nThe AI work\nAI is core to our product, but we don't run agents for everything. We use them where they create real value. For that we built our own LLM harness from hard-earned production experience: maximum freedom for the model, without compromising on enterprise control, governance or EU data residency.\nWhat this means for you: you work hands-on with these new technologies, you run evals instead of trusting demos, and you know how to put this stuff into production reliably. Agent output gets benchmarked against expert-curated baselines, and failure modes get named, measured and fixed. If you are obsessed with how AI systems behave, fail and improve, this is the place for you.\nHow we ship\nSmall teams of 2 to 3 engineers around a topic. We deploy continuously to production.\nWe use AI tools heavily, and you have freedom in which ones (e.g. Cursor, Claude, Codex). Around that we run a strong operating system: clear ticket context, focused branches, AI review before human review, screenshots or videos for product changes, manual product testing before release, production verification after.\nThe engineer who ships a change owns it in production. If something breaks, you lead the fix.\nRequirements\nWhat we need from you\nNobody at 11 people knows everything. We hire people who dive in and own outcomes.\n3 to 6 years of full-stack experience shipping production software people actually use.\nYou can get productive in our stack fast: Kotlin/Spring Boot and Python on the backend, TypeScript/React on the frontend. You don't need to know all of it on day one, but you should get into it quickly.\nYou have shipped agentic systems, side projects absolutely count. You think in tools, context and evals, not just prompts.\nFluent English. German is a real plus because many customer calls run in German. We pair you with a German-speaking teammate when needed, but German gets you closer to users faster.\nYou'll stand out if\nYou build with AI natively, not as an afterthought.\nYou can take a vague problem to a shipped feature. You scope, decide, implement, test and iterate.\nYou want to understand why people behave the way they do, and you use that understanding to make product decisions.\nYou have high standards for yourself and move fast without needing to be pushed. B2B SaaS or startup experience is a plus.\nOur stack\nKotlin (Spring Boot) & Python · TypeScript (React/Next.js) · PostgreSQL · AWS (Fargate, ECS) & Terraform · GitHub Actions · Azure (OpenAI) · AWS (Bedrock)\nBenefits\nWorking here\nWe work from our office in Berlin (hybrid, but most engineering happens in-person). The team spends free-time together several times a month, shares lunch, and works closely on hard problems. No politics, no long meetings - we move fast and make decisions at the whiteboard. You'll be one of 11 people, which means your work ships to customers within days, not quarters.\nBenefits\nAttractive compensation package including employee stock options\nHybrid work with a modern office in Berlin\n30 days of vacation and day off on your birthday\nBudget for self-improvement and dedicated time for learning & innovation\nHome-office allowance, Deutschlandticket, gym pass\nThe best popcorn in town\nReady to make an impact? 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