ai engineer (m/f/d)

full stack engineer

senior data engineer

senior product engineer

ai engineer — genai & agentic solutions (m/w/d) amazon web services Jobs in Berlin

full stack ai engineer

mLabs

<div>Location: Remote - If based in NYC, will require office presence 2/3 days a week, for LATAM and European regions will be expected to work EST hours with a 5 hour overlap.
Remote/Hybrid | Full-time
Compensation: $140K - $200K
We are hiring on behalf of our client, an innovative technology firm who is seeking an experienced Full-Stack AI Engineer to join a growing, AI-focused engineering team. The client develops advanced intelligence and analytics solutions designed to help participants in digital asset markets make more informed decisions by combining financial data, automation, and modern AI technologies to transform complex information into actionable insights.
In this role, the successful candidate will work closely with product, research, and engineering leadership to develop next-generation, AI-powered financial applications. This is a highly collaborative position that requires strong ownership, technical depth, and the ability to move quickly from concept to production.
Key Responsibilities
Full-Stack Product Development<ul><li>
Architecture &amp; Maintenance: Architect, develop, and maintain end-to-end applications powering AI-driven financial products.</li><li>
Backend &amp; APIs: Build scalable backend services and APIs that support intelligent workflows and automated decision-making.</li><li>
UI Development: Create intuitive, high-performance user interfaces that surface complex insights and enable interactive experiences.</li><li>
Real-Time Systems: Design systems that support real-time communication between users, data sources, and AI components.</li></ul>
AI &amp; Data Integration<ul><li>
Cross-Functional Collaboration: Partner with research and machine learning teams to integrate AI capabilities into production environments.</li><li>
Data Pipelines: Implement and maintain pipelines that ingest, process, and manage structured and unstructured financial data.</li><li>
Operationalization: Support the deployment and operationalization of AI-powered features and workflows.</li></ul>
Engineering Excellence<ul><li>
Standards &amp; Reliability: Establish testing, observability, monitoring, and reliability standards across applications and services.</li><li>
Optimization: Optimize system performance, scalability, and maintainability.</li><li>
Technology Evaluation: Evaluate and adopt emerging technologies across AI, software engineering, and financial infrastructure.</li></ul>
Continuous Learning<ul><li>
Industry Trends: Stay informed on developments in large language models, agent frameworks, financial technologies, and modern web architectures.</li><li>
Best Practices: Contribute to technical discussions and help shape engineering best practices across the organization.</li></ul> 

Requirements 
Required Qualifications<ul><li>
Experience: 5+ years of professional experience building full-stack applications.</li><li>
Backend Expertise: Strong programming experience with Python, including modern API frameworks such as FastAPI. Advanced proficiency in JavaScript and TypeScript, with extensive experience developing applications using Node.js.</li><li>
Frontend Expertise: Advanced proficiency in React for building user interfaces.</li><li>
System Design: Demonstrated success building scalable web platforms, APIs, and backend services, alongside a strong understanding of both relational and non-relational database technologies.</li><li>
AI &amp; Agent Architecture: Deep knowledge of prompt design, tool-calling architectures, Model Context Protocol (MCP), and agent orchestration patterns. Experience deploying and operating AI agents or autonomous workflow systems in production environments.</li><li>
Information Retrieval: Experience building embedding pipelines, semantic retrieval systems, and advanced search capabilities. Familiarity with vector search technologies, retrieval-augmented generation (RAG), and asynchronous application patterns.</li><li>
AI Frameworks: Hands-on experience developing solutions using large language models and AI orchestration frameworks (e.g., LangChain or comparable technologies).</li><li>
Domain Knowledge: Experience working with financial datasets, market data, or financial service APIs.</li><li>
Professional Attributes: Ability to operate comfortably in fast-moving environments with significant autonomy and ownership.</li></ul>
Preferred Qualifications<ul><li>
Location: Located in the United States, Latin America, or Europe, with flexibility to collaborate across time zones.</li><li>
Performance Tuning: Strong understanding of application profiling, scalability optimization, and performance tuning.</li><li>
Track Record: A history of success within high-growth, collaborative engineering organizations.</li><li>
Digital Assets: Exposure to blockchain infrastructure, smart contracts, decentralized finance (DeFi), or digital asset ecosystems.</li></ul> 

Benefits 
<ul><li>
Competitive compensation package.</li><li>
Opportunity to work at the intersection of cutting-edge AI and digital asset markets.</li><li>
Highly autonomous and collaborative work environment.</li><li>
Remote-friendly flexibility across eligible regions.</li></ul> 
Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.
Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.
MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd&rsquo;s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.</div>

Full Stack AI Engineer

Chapter 2

<div>Senior Product Engineer &ndash; Digital Health / AI Berlin (on-site) &middot; Full-time
Chapter 2 is partnering exclusively with a leading digital health startup at the forefront of AI-enabled cardiac telemonitoring. Working with institutions including Charit&eacute;, Mayo Clinic, and UCSF, they are building technology that detects early signs of heart failure deterioration and improves patient outcomes at scale.
They are looking for a Senior Product Engineer to join a small, high-ownership team and take end-to-end responsibility for significant product projects across their AI-enabled platform.
The Role
You will work closely with the Product Lead to scope, build, and ship substantial features across the full stack, from physician and patient interfaces on the frontend to APIs, data modelling, and ML integration on the backend. You won't be handed tickets. You'll shape projects from concept through to post-launch iteration, lead a small squad of engineers, and collaborate directly with clinical partners, sales, and founders.
What You'll Need<ul><li>
M.Sc. in a STEM field with 2+ years of full-stack experience, or 4+ years without</li><li>
Strong Python on the backend, TypeScript/React on the frontend</li><li>
A product and user-focused mindset &mdash; you care about UX and make design decisions, not just implementation decisions</li><li>
Comfort operating with high autonomy in a small team</li><li>
Fluent English</li></ul>
Nice to Have<ul><li>
Experience with ML/data pipelines, audio/signal processing, or clinical data</li><li>
Background in regulated software (MDR, ISO 13485, IEC 62304) or healthcare products</li><li>
DevOps and cloud infrastructure experience (GCP, CI/CD)</li><li>
German language skills</li></ul>
What's on Offer<ul><li>
Competitive compensation package with meaningful equity</li><li>
A mission that matters &mdash; technology with direct impact on patient outcomes</li><li>
A Berlin-Mitte office and a team built from some of the best engineering and clinical minds in digital health</li><li>
Urban Sports Club membership</li></ul>
If you are a full-stack engineer who wants to own real product work in a clinical environment that is genuinely changing how heart disease is managed, we'd like to hear from you.</div>

Senior Product Engineer

<div>Chapter 2 is partnering exclusively with a leading digital health startup at the forefront of AI-enabled cardiac telemonitoring. Working with institutions including Charit&eacute;, Mayo Clinic, and UCSF, they are building technology that detects early signs of heart failure deterioration and improves patient outcomes at scale.
They are looking for a Full Stack Engineer to join a small, high-ownership team and take end-to-end responsibility for significant product projects across their AI-enabled platform.
The Role
You will work closely with the Product Lead to scope, build, and ship substantial features across the full stack, from physician and patient interfaces on the frontend to APIs, data modelling, and ML integration on the backend. You won't be handed tickets. You'll shape projects from concept through to post-launch iteration, lead a small squad of engineers, and collaborate directly with clinical partners, sales, and founders.
What You'll Need<ul><li>
M.Sc. in a STEM field with 2+ years of full-stack experience, or 4+ years without</li><li>
Strong Python on the backend, TypeScript/React on the frontend</li><li>
A product and user-focused mindset, you care about UX and make design decisions, not just implementation decisions</li><li>
Comfort operating with high autonomy in a small team</li><li>
Fluent English</li></ul>
Nice to Have<ul><li>
Experience with ML/data pipelines, audio/signal processing, or clinical data</li><li>
Background in regulated software (MDR, ISO 13485, IEC 62304) or healthcare products</li><li>
DevOps and cloud infrastructure experience (GCP, CI/CD)</li><li>
German language skills</li></ul>
What's on Offer<ul><li>
Competitive compensation package with meaningful equity</li><li>
A mission that matters, technology with direct impact on patient outcomes</li><li>
A Berlin-Mitte office and a team built from some of the best engineering and clinical minds in digital health</li><li>
Urban Sports Club membership</li></ul>
If you are a full-stack engineer who wants to own real product work in a clinical environment that is genuinely changing how heart disease is managed, we'd like to hear from you.</div>

Full Stack Engineer

Wolters Kluwer

<div>As a Senior Full Stack Engineer (m/f/d) , you will be working for our Legal &amp; Regulatory division where we help legal and compliance professionals enhance productivity, mitigate risk, and solve complex problems confidently. 
There are hundreds of thousands of lawyers across Europe &mdash; and at Libra, we&rsquo;re transforming how they work. Our AI platform combines deep legal reasoning with cutting-edge generative technology, fundamentally changing how lawyers research, draft, and deliver legal work. 
About the role
We are looking for exceptional engineers to join our fast-growing team automating knowledge work for legal professionals. As a Full Stack Engineer, you&rsquo;ll play a central role in developing our product and have high impact and ownership over key product features. You&rsquo;ll work end-to-end across the stack, contributing to both backend and frontend development in a lean, agile environment.
This is a unique opportunity to shape the future of legal tech by building intelligent, scalable solutions that empower professionals and transform workflows. 
In your role you&rsquo;ll be part of high skilled technology organization and a fast growing product organization. An ambitious and thrilling place to be as you&rsquo;ll be essential to both strategic alignment and local execution. You&rsquo;ll be working at the vibrant Merantix AI Campus in Berlin, surrounded by a community of AI innovators. We value collaboration, curiosity, and a bias toward action. 
What you&rsquo;ll do:<ul><li>
Design, implement, and maintain product features across the stack&mdash;from backend APIs to frontend interfaces.</li><li>
Collaborate closely with product and design teams to deliver intuitive, high-performing user experiences.</li><li>
Ensure code quality, security, and scalability through best practices and thoughtful architecture.</li><li>
Contribute to technical decision-making and help shape the engineering culture.</li><li>
Explore and integrate AI tools and agents to enhance developer productivity and product capabilities.</li></ul> 
What you&rsquo;ll bring: 
Education<ul><li>
Bachelor's degree preferred in Computer Science or Software Engineering or similar disciplines.</li></ul> 
Experience<ul><li>
Minimum 4 years of relevant experience working within product software engineering.</li><li>
Strong experience with Python, particularly FastAPI and asynchronous programming.</li><li>
Solid proficiency in TypeScript; experience with Svelte is a strong plus.</li><li>
Familiarity with software engineering best practices and security principles.</li><li>
Experience using AI coding agents like Cursor or Claude Code.</li><li>
Bonus: You&rsquo;ve built or contributed to LLM-powered products.</li></ul> 
Skills<ul><li>
Entrepreneurial mindset with strong ownership and urgency.</li><li>
A pragmatic approach to problem solving. It&rsquo;s more important to you to solve the problem than to use new/hyped technology.</li><li>
Accountability and commitment to high-quality outcomes.</li><li>
Excellent communication in English; German is a plus.</li></ul> 
Working together
This is a hybrid role, where you will spend at least eight days a month at our office, where you'll enjoy the benefits of connecting and collaborating with your colleagues in person. 
What we offer<ul><li>
Permanent employment from day one.</li><li>
Remote work &amp; flexibility: Work remotely up to 3 days per week (home office) (= 8 days a month in the office) with flexible working hours.</li><li>
Work abroad flexibly: Work from anywhere within the EU for up to 20 days within a twelve-month period.</li><li>
Rest &amp; time off: 26 vacation days.</li><li>
Show your commitment: 1 additional day off per year for your volunteer work (Volunteer Day).</li><li>
Support for development: E-learning via LinkedIn, online language training with goFluent, and other training and development opportunities.</li></ul> 
In just over a year, we&rsquo;ve established ourselves as Europe&rsquo;s fastest-growing legal AI company by partnering with leading law firms, corporate legal departments, and publishers, As part of Wolters Kluwer&rsquo;s Legal &amp; Regulatory Division, Libra is building the operating system for modern legal work &mdash; and you can help us write its next chapter.
#LI-Hybrid
<h2 class="jobSectionHeader">Our Interview Practices</h2>
To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we&rsquo;re getting to know you&mdash;not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.
Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.</div>

Senior Full Stack Engineer (Libra - Legal AI Assistant) (m/f/d)

THRYVE

<div>
 
 
 Product Engineer (Full Stack/AI) Berlin | On-site/Hybrid
 
 
 
 
 
 
 We're partnering with an ambitious health-tech startup building AI-powered software that helps clinicians make better decisions and improve patient outcomes, working on one of the hardest and most meaningful challenges in healthcare: turning complex clinical data into products that help medical teams identify risk earlier, intervene faster, and ultimately improve lives.
 
 
 
 
 
 We're looking for a strong engineer who wants to own products, not tickets.
 
 
 
 
 
 You'll work across backend, frontend, AI integrations, and product strategy, taking features from idea to production. You'll collaborate directly with founders, designers, clinicians, and engineers to solve complex technical problems and ship software that genuinely matters.
 
 
 
 
 
 
 What You'll Work On
 
 
 <ul>
 <li>
 Building production-grade AI features and workflows
 </li>
 <li>
 Designing scalable backend systems and APIs in Python
 </li>
 <li>
 Developing modern React/TypeScript applications
 </li>
 <li>
 Integrating machine learning models into real-world products
 </li>
 <li>
 Working with complex, high-value healthcare data
 </li>
 <li>
 Improving reliability, observability, testing, and engineering quality across the platform
 </li>
 </ul>
 
 
 
 
 
 We're Looking For
 
 
 <ul>
 <li>
 Strong software engineering fundamentals
 </li>
 <li>
 Professional experience with Python and React/TypeScript
 </li>
 <li>
 Product-minded engineers who enjoy understanding user problems
 </li>
 <li>
 Builders who take ownership and thrive in small, high-performing teams
 </li>
 <li>
 Engineers excited by AI-enabled products and difficult technical challenges
 </li>
 <li>
 M.Sc. in a STEM field
 </li>
 </ul>
 
 
 
 
 
 Nice To Have
 
 
 <ul>
 <li>
 Experience with AI/ML systems
 </li>
 <li>
 Cloud infrastructure and DevOps experience
 </li>
 <li>
 Exposure to healthcare, regulated software, or data-intensive products
 </li>
 </ul>
 
 
 
 
 
 Why Join?
 
 
 <ul>
 <li>
 Build technology with real-world impact
 </li>
 <li>
 Work directly with exceptional founders and engineers
 </li>
 <li>
 Own major product initiatives end-to-end
 </li>
 <li>
 Solve technically challenging problems at the intersection of software, AI, and healthcare
 </li>
 </ul>
 
 
 
 
 If you're the kind of engineer who enjoys moving quickly, taking ownership, and building products from the ground up, we'd love to hear from you.
 
</div>

GTM Base

<div>RevOps is changing fast, and so is the way GTM processes get built and maintained inside the CRM. This role puts you on the front edge of it: forward-deployed in our clients' RevOps teams, building and running their GTM systems in a genuinely AI-first environment.

GTMBase is an AI-first GTM engineering and RevOps agency. We help post-PMF B2B companies (&euro;8M to &euro;50M ARR, 5+ reps) whose go-to-market is over-performing their systems. Reps do manually what should be automated, sales and marketing data doesn't connect, and leadership can't trust the reporting.

We combine strategic GTM thinking with hands-on technical build, and we fix the foundation before running campaigns.

We deliver across Four Pillars:
<div>
<ul><li>Data Foundation: list building and enrichment so reps win with better data (Clay, Apollo, custom scrapers, AI research)</li></ul>
<ul><li>RevOps &amp; CRM: building the right GTM process inside the client's CRM, including architecture, lifecycle, pipelines, routing, and reporting (HubSpot, Salesforce)</li></ul>
<ul><li>Agentic Workflows: building agentic GTM workflows with Anthropic Managed Agents and Hermes, getting the org ready for Agentic GTM</li></ul>
<ul><li>GTM Strategy &amp; Plays: recommending and executing the highest-impact campaigns</li></ul>
</div>
We've done this for clients including Groupon, Blinkist, Booksy, and Sendify. We work in small pods, with a Strategist, a CRM Architect, and a GTM Engineer.
<h2 class="jobSectionHeader">
How We Operate</h2>

We run the company on Claude Code. It's our operating system: client context, playbooks, automations, and delivery all live in it, and AI is the default way we work rather than a bolt-on. You'll work this way too, and get very good at it.
<h2 class="jobSectionHeader">
Why This Role Matters</h2>

You're the person who turns our GTM strategy into a CRM that actually works. Most clients run their entire revenue motion on HubSpot or Salesforce, and the quality of that system runs through this role: how clean the data is, how well leads route, whether leadership can trust the reporting.

Here, &quot;Architect&quot; means architecting inside the CRM: the object model, pipelines, workflows, and automations. The GTM and revenue strategy is set with you in your pod, not by you alone, and you build it with real craft.

You're forward-deployed: you embed with clients' RevOps and sales teams and build inside their live CRM.
<h2 class="jobSectionHeader">
The Role</h2>

You'll build and maintain GTM process and automation inside our clients' CRMs, mostly HubSpot. Working from the direction set in your pod, you turn requirements into a clean, well-built system the sales team can rely on.

One week you're building a client's lead lifecycle and routing. The next you're debugging a broken automation, untangling duplicate deals, or shipping a dashboard a CRO asked for. You move across several client instances at once without dropping threads.

You're a builder with an admin's discipline. You know the object model, not just the UI. You sweat the details others miss, you test before you ship, and you document what you build so the rest of the pod can run it. When something breaks, you find the root cause and fix it properly.
<h2 class="jobSectionHeader">
How This Differs From a GTM Engineer</h2>

Your pod is you (CRM Architect), a Strategist who sets direction and hands you requirements, and a GTM Engineer. You and the GTM Engineer are both builders, but you own different layers:
<ul>
<li>You (CRM Architect, Pillar 2): the GTM process inside the CRM. HubSpot/Salesforce architecture, lifecycle, routing, deal logic, automation, reporting, data integrity. You live in HubSpot, Salesforce, Operations Hub, and n8n.</li>
<li>GTM Engineer (Pillar 1): the data layer. Enrichment, scraping, signal detection, list building, custom research agents. They live in Clay, Apify, custom scrapers, and data APIs.</li>
</ul>
Think of it as the data into the CRM (GTM Engineer) versus the system it lands in and the process the sales team runs on (you). You don't need to be a Clay or Apify expert. You just need a solid working understanding of what a GTM Engineer does, enough to spec what you need, integrate their output cleanly, and know what's possible.
<h2 class="jobSectionHeader">
What You'll Do</h2>
<ul><li>Architect and build in client HubSpot instances: information architecture (objects, associations, lifecycle stages, pipeline structure), workflows, deal logic, lead scoring, routing, properties, and permissions</li>
<li>Build and debug automations across the GTM stack: HubSpot workflows, n8n, APIs, and webhooks. When an automation breaks, you find the root cause rather than just toggling features</li>
<li>Guard data integrity: deduplication, field validation, association hygiene, and import discipline so reporting and forecasting can be trusted</li>
<li>Build the reporting leadership relies on: pipeline coverage and velocity, stage-by-stage conversion, and full-funnel dashboards. You know where HubSpot's platform and paywall limits force a different approach</li>
<li>Design integrations and data flows between HubSpot and the rest of the stack (Clay, Aircall, telephony, billing, enrichment pipelines)</li>
<li>Turn requirements into working builds: take a brief like a 15-minute lead-response SLA and ship the routing system that delivers it</li>
<li>Keep multiple client instances healthy at once, with fast turnaround and nothing falling through the cracks</li>
<li>Work client-facing: you can talk through a data question with a technical lead and walk a frustrated AE through a new flow in the same afternoon</li>
<li>Codify what works into our library of reusable plays and patterns, so every client build sharpens the whole team</li>
</ul><h2 class="jobSectionHeader">What We're Looking For</h2>

Must-have
<ul>
<li>Deep HubSpot expertise: hands-on across Sales, Marketing, Service, and Operations Hubs. You know HubSpot well enough to know what is and isn't possible at the platform level, and to choose native functionality over a workaround when it's the right call.</li>
<li>Strong CRM and RevOps fundamentals: lead lifecycle and qualification, routing and assignment, pipeline and deal-stage setup, the data model, and the governance that keeps it clean.</li>
<li>An admin's discipline: precise, reliable, and detail-obsessed. You test before you ship, you keep data clean, and you don't let things fall through the cracks.</li>
<li>A builder's instinct: you build workflows and integrations, debug them when they break, and aren't intimidated by APIs, webhooks, or a tool you haven't used yet.</li>
<li>AI-first, and we mean it literally: AI is your default operating mode, not a novelty. Your first move on a problem is to reach for an agent, a prompt, or a workflow before a manual process. If you're not already using AI tools daily, this isn't the right fit. (If your CRM fundamentals are deep but your GTM-tooling experience like Clay or Claude Code is light, that part is learnable and we'll back you on it. The fundamentals and the AI-first instinct are not.)</li>
<li>Forward-deployed temperament: comfortable building across multiple clients in parallel, client-facing, proactive, and able to move fast without waiting for perfect requirements.</li>
<li>Full-time availability with reliable overlap to CET hours.</li>
</ul>
Nice-to-have
<ul>
<li>Salesforce: admin or build experience, especially HubSpot to Salesforce sync and migrations (relevant to Groupon and enterprise work)</li>
<li>A working understanding of the GTM Engineer's toolkit: Clay, Apify, enrichment providers (ZoomInfo, Apollo, Clearbit), scraping. Enough to collaborate, spec, and integrate. Your pod's GTM Engineer owns the deep builds.</li>
<li>n8n orchestration and custom API integrations</li>
<li>Scripting (Python, SQL, or JavaScript) for data manipulation and custom connectors</li>
<li>German: a good chunk of our client base is DACH</li>
<li>HubSpot certifications: a plus, never a gate. Demonstrated depth matters more.</li>
</ul><h2 class="jobSectionHeader">What You'll Get</h2>
<ul><li>Real client build work from day one, with no busy work and no hand-holding</li>
<li>A front-row seat in a genuinely AI-first environment: Claude Code as the operating system, Clay, and the full modern GTM stack</li>
<li>Direct collaboration with one of the most experienced RevOps leaders in Europe</li>
<li>Exposure to a wide range of B2B companies, stacks, and GTM problems</li>
<li>A seat at the table in a growing practice, not a cog in a machine</li></ul></div>

Forward-Deployed CRM Architect

Stackgini

<div>
 
 At Stackgini we are turning business ideas into technology impact.
 
 
 
 In most large companies this journey is broken. A good idea lands in an IT organization that runs hundreds of applications, and nobody can tell you quickly what already exists, what is redundant or what to buy. So decisions happen in spreadsheets and gut feeling, and ideas wait.
 
 
 
 We are changing that. Our platform understands the enterprise application landscape bottom-up, from individual demands to full portfolio interdependencies, and reasons about it the way the best human experts do, just at machine scale. Our vision: enterprise IT that is self-governing and self-optimizing. No longer a bottleneck, but the engine of innovation.
 
 
 
 We are 11 people, and we build this with Siemens Healthineers, REWE, SAP, DATEV, Danaher and other leading enterprises including even more DAX 40 and Fortune 500 companies. We have thousands of users and process very large IT landscapes, one of our customers even exceeds 11,000 applications. At this size there is no hiding. What you ship goes to customers fast, and the people who join now set the standard for the product, the culture and the category.
 
 
 Tasks
 
 
 
 The role
 
 
 
 
 A Product Engineer at Stackgini owns features end to end. You take a customer problem, scope it with Product &amp; 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.
 
 
 
 You 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.
 
 
 
 We 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.
 
 
 
 
 The AI work
 
 
 
 
 AI 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.
 
 
 
 What 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.
 
 
 
 
 How we ship
 
 
 
 <ul>
 
 <li>
 Small teams of 2 to 3 engineers around a topic. We deploy continuously to production.
 </li>
 
 <li>
 We 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.
 </li>
 
 <li>
 The engineer who ships a change owns it in production. If something breaks, you lead the fix.
 </li>
 
 </ul>
 
 Requirements
 
 
 
 What we need from you
 
 
 
 
 Nobody at 11 people knows everything. We hire people who dive in and own outcomes.
 
 
 <ul>
 
 <li>
 3 to 6 years of full-stack experience shipping production software people actually use.
 </li>
 
 <li>
 You 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.
 </li>
 
 <li>
 You have shipped agentic systems, side projects absolutely count. You think in tools, context and evals, not just prompts.
 </li>
 
 <li>
 Fluent 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.
 </li>
 
 </ul>
 
 
 
 You'll stand out if
 
 
 
 <ul>
 
 <li>
 You build with AI natively, not as an afterthought.
 </li>
 
 <li>
 You can take a vague problem to a shipped feature. You scope, decide, implement, test and iterate.
 </li>
 
 <li>
 You want to understand why people behave the way they do, and you use that understanding to make product decisions.
 </li>
 
 <li>
 You have high standards for yourself and move fast without needing to be pushed. B2B SaaS or startup experience is a plus.
 </li>
 
 </ul>
 
 
 
 Our stack
 
 
 
 
 Kotlin (Spring Boot) &amp; Python &middot; TypeScript (React/Next.js) &middot; PostgreSQL &middot; AWS (Fargate, ECS) &amp; Terraform &middot; GitHub Actions &middot; Azure (OpenAI) &middot; AWS (Bedrock)
 
 
 Benefits
 
 
 
 Working here
 
 
 
 
 We 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.
 
 
 
 
 Benefits
 
 
 
 <ul>
 
 <li>
 Attractive compensation package including employee stock options
 </li>
 
 <li>
 Hybrid work with a modern office in Berlin
 </li>
 
 <li>
 30 days of vacation and day off on your birthday
 </li>
 
 <li>
 Budget for self-improvement and dedicated time for learning &amp; innovation
 </li>
 
 <li>
 Home-office allowance, Deutschlandticket, gym pass
 </li>
 
 <li>
 The best popcorn in town
 </li>
 
 </ul>
 
 
 Ready to make an impact? Join us at Stackgini and be part of something extraordinary!
 
</div>

Product Engineer (m/f/d)

Explore 153+ Full stack ai engineer in Berlin this July. Find roles across top companies and apply now to boost your career.

153 full stack ai engineer jobs In Berlin

Full Stack AI Engineer

Senior Product Engineer

Full Stack Engineer

Senior Full Stack Engineer (Libra - Legal AI Assistant) (m/f/d)

Full Stack Engineer

Forward-Deployed CRM Architect

Product Engineer (m/f/d)