AI Platform Engineer

Modaxo; Deutschland; On-site; EUR 95,000 - 140,000; Full time

Job summary

Modaxo is seeking a senior platform engineer to design and build core backend services, including APIs and orchestration, for an enterprise AI platform. You will contribute to the reference architecture and own delivery from design to on-call support.

You will join a small, senior founding team building from the ground up, balancing platform reuse with product velocity while driving reliability and customer value.

Qualifications

• Experience building production backend or distributed services relied on by other teams.
• Own correctness, tests, and operations for what you build.
• Explain systems by the trade-offs you made, not just the technologies you used.
• Communicate clearly with engineers, product partners, and customers, and bring people along.
• Focus on outcomes and value and make pragmatic calls to ship.

Responsibilities

• Design, implement, test, deploy, and own services end to end.
• Shape API design and developer experience for internal and external consumers of the platform.
• Ensure boundaries are clean so components stay swappable and scalable.
• Build data and integration on-ramps with reliable connectors and proper governance.
• Mentor teammates, raise the bar as we grow, and foster technical excellence.

Skills

Production distributed systems

End-to-end ownership

Trade-off reasoning

Clear communication

Value and pragmatism

Job description

At Modaxo, we're passionate about changing the face of people transportation. We believe that all transportation services should be safe, efficient, convenient, and equitable. Our products power mission-critical operations across a variety of industry sectors. We're making a strategic investment in AI to transform our solutions.

You will build the core services of a new enterprise AI platform - the APIs, orchestration, and data and integration on-ramps that our products build on. We ship working software on aggressive timelines; perfect is the enemy of shipped.

You'll report to the Head of AI Platform Engineering and join a small, senior founding team building the platform from the ground up.

The opportunity: build the services an entire product portfolio depends on, with a clean slate and real ownership.

Why this role is different

• It's platform AND product. You build reusable platform capability while enabling product teams to ship features fast - balancing leverage with velocity.
• It's domain-first, not tech-first. You'll learn our customers' operational domain; the best platform choices come from understanding how the work actually runs.
• It's pragmatic build/buy. We win on integration and reliability using proven components - pragmatic decisions, not gold-plating.
• It's a founding role - you help build the team. As an early hire you'll set the patterns, tests, and guardrails others build on, and help raise the bar as we hire.
• It's production-first, not research-first. We ship on aggressive timelines and own what we ship.
• It's value-based. You'll validate with product teams and customers and prioritize by value - building what moves outcomes, not what's novel.

What You'll Do

Core Platform Services

• Design and build core backend services - APIs, orchestration, and access control - as reliable, well-tested production systems.
• Shape API design and developer experience for internal and external consumers of the platform.
• Contribute to the reference architecture and design records; keep boundaries clean so components stay swappable.
• Build for multiple customers on shared infrastructure: isolation, quotas, and usage metering done properly.
• Build data and integration on-ramps - connector frameworks and governed data access that are idempotent and reliable at scale.

Ownership & Reliability

• Own services end to end: design, implementation, tests, deployment, and on-call for what you ship.
• Model failure modes explicitly - partial failure, retries, consistency, back-pressure - and design for them.

Delivering Value with Product & Customers

• Work with product teams and customers to validate results and outcomes, prioritizing by value.
• Take a value-based development approach: prove value with the smallest useful slice, then scale what works.
• Instrument and measure impact; let evidence - not opinion - drive what ships.
• Build automated QA - tests, quality gates, and regression checks - into the delivery pipeline.

Building the Team & Ways of Working

• Help build the team: contribute to hiring, raise the bar in interviews, and mentor as we grow.
• Foster a culture of technical excellence, customer obsession, and pragmatic shipping.
• Partner with product teams across the portfolio who own their own roadmaps.

What You'll Bring

We look at demonstrated experience and scope, not years served - and we don't expect every candidate to tick every box.

• Production distributed systems: You've built and operated production backend or distributed services that other teams depend on.
• End-to-end ownership: You own correctness, tests, and operations for what you build.
• Trade-off reasoning: You describe systems by the trade-offs you made, not just the technologies you used.
• Clear communication: You explain your thinking clearly to engineers, product partners, and customers, and bring people along.
• Value and pragmatism: You focus on outcomes and value and make pragmatic calls to ship.

Bonus Points

Any of these strengthen an application - none are required:

• Multi-tenant SaaS: Backend services serving many customers with enforced isolation and metering.
• Gateways & orchestration: API gateways or workflow orchestration at scale.
• Integration frameworks: Connector or integration frameworks (API/EDI/CDC), not one-off scripts.
• LLM-backed services: Backend work behind AI or LLM features in production.
• Languages: Strength in C#/.NET or Python; Go a bonus.
• Architecture experience: System/platform design and trade-off judgement - one-way vs two-way doors.
• Enterprise scale: Experience building or operating enterprise-scale software and its reliability, security, and integration demands.
• AI-assisted engineering: You use AI coding assistants productively and supervise their output with judgement.

New to some of this? If you bring the essentials above and are excited by the problem, we'd still like to hear from you.