We are looking for a forward-thinking Senior AI Software Engineer to drive intelligence into our core products and internal operations. Sitting at the intersection of robust backend engineering and advanced AI, you will design, scale, and productionize our custom, in-house agentic stack, leveraging LLMs and event-driven microservices to solve real-world mobility challenges across Europe.
Activities
- Take Peter Park's agentic capabilities to the next level: designing, building, and scaling AI agents and LLM-powered systems that solve concrete problems across product, tech, operations, and the wider business.
- Set the standard for technical excellence in AI engineering: when agents write the code, your edge is judgment - maintainable systems, sharp evaluations, GDPR-compliant data handling, and architectures built to last.
- Transform how we work with AI: lead the practical adoption of AI across the company by building our in-house agentic stack. You’ll turn raw LLMs and AI agents into reliable production systems, running live pilots and enabling teams to safely leverage AI tools in their daily workflows.
- Apply that stack where it creates measurable impact: internal knowledge management, workflow automation across departments, and AI-supported business intelligence.
- Embed LLM-powered intelligence into our core product where it strengthens our barrier-free parking platform.
- Own selected AI workstreams end-to-end: from problem framing with stakeholders, through architecture and implementation, to deployment, measurement, and iteration.
- Propose and drive the technical roadmap for our agentic AI capabilities together with the CTO and Team Leads, and represent AI direction in cross-functional forums.
- Drive projects & develop talent: take ownership of major initiatives from concept to delivery. As a senior engineer, you’ll guide team members through technical challenges and champion an environment where everyone keeps leveling up.
Requirements
- Strong backend engineering background with proficiency in TypeScript and/or Python, and experience building production microservices and event-driven systems on cloud infrastructure.
- Hands-on experience designing and shipping LLM-powered or agentic systems: multi-step tool use, retrieval, evaluation, prompt and context engineering, safety and guardrails. Not just an API wrapper.
- Comfort with modern AI-assisted development tools (e.g. Claude Code, Cursor, Copilot) and an opinion on where they help, where they don't, and how to scale their use across a team.
- Familiarity with at least one of: vector and hybrid retrieval, MCP or similar agent-tool protocols, model evaluation and observability.
- Track record of taking ownership end-to-end: from talking to the business about the real problem, through architecture and delivery, to measuring impact and iterating.
- A pragmatic, experimentalmindset: comfortable with ambiguity, able to make crisp trade-offs between accuracy, latency, cost, and time-to-market. You focus on momentum, with a strong willingness to pivot away from non-working approaches in favor of shipping continuous, meaningful feature iterations.
- Awareness of the responsible-AI dimension: data privacy (especially GDPR and EU data residency), security, and clear human approval points where they belong.
- Naturally collaborative: you translate complex AI concepts into language product owners, operators, developers and execs can act on, and bring people along rather than working in a corner.
- Eagerness to influence beyond your own code: spotting friction in how the company works and turning it into automated, intelligent workflows.
- Fluent EnglishGerman is a plus, not a requirement.
Technologies We Work With:
- AI stack: frontier LLM APIs (Anthropic, OpenAI, Google), hybrid retrieval and vector search, MCP-based agent tooling, evaluation frameworks, and an in-house event-driven agentic platform powering automated workflows.
- Event-driven backend development in Python and NestJS (Microservice architecture).
- Frontend monorepo with Turbo, pnpm, and Storybook, primarily using Vue.js.
- TypeScript, BullMQ, and Prisma in an opinionated monorepo approach.
- Cloud infrastructure on AWS (RDS, DynamoDB, S3, Lambda, EC2, SQS).
- Container orchestration with Kubernetes and IaC using Terraform.
- CI/CD pipelines via GitLab and monitoring via Datadog.
- Edge & IoT Infrastructure: Thousands of distributed devices (kiosks, tablets, cameras) deployed across Europe.
Team
Work Setup:
- Hours: 40 hours per week (based on trust).
- Home Office Policy: Enjoy a hybrid model with 3 days in the office / 2 days remote.
- Contract: A permanent contract for long-term stability.
- Location: Our modern office in Munich, a vibrant city in the heart of Bavaria.
Application Process
- Initial Contact: We’ll get back to you within 48 hours.
- HR Interview: Discuss your experience and expectations with our HR team.
- Live Assessment: Showcase your skills in a practical technical challenge.
- Tech Challenge: Tackle a problem in a familiar context to demonstrate your technical skills and approach.
- Leadership Conversation: A deep dive into the role and expectations with a member of our technical leadership.
- On-Site Meeting: Visit our Munich office, meet more of the team, and experience our culture firsthand!