Own NALAβs AWS cloud foundation and build a shared platform that improves reliability, security, observability, and developer velocity across its B2B and B2C products.
Senior Platform Engineer
π Description
- Integrate AI products that process data from external sources and multiple systems in real time.
- Route streaming responses and language model requests across providers, with fallback and cost controls.
- Monitor latency, costs, and error rates, and proactively address issues.
- Make architectural decisions that balance system quality with simple, maintainable designs.
- Build application code alongside platform and operational work; investigate production issues through instrumentation and root-cause analysis.
π οΈ Requirements
- At least 3 years of production backend engineering experience, including substantial TypeScript experience and ownership of production systems.
- Production experience with Docker and Kubernetes, plus solid knowledge of PostgreSQL, APIs, queues, and caching.
- Strong system design skills and the ability to reason about performance, latency, reliability, and cost trade-offs.
- Experience improving platform reliability and performance under production load, and building observability to diagnose complex systems.
- Experience with streaming responses or language model request routing across providers is valuable.
- Comfort contributing to frontend code when needed, and experience with CI/CD, safe deployments, and incident follow-up is beneficial.
Full job description
About the Role
Join an AI product engineering team building a platform that connects data sources and supports real-time workflows. You will shape the platform foundations, helping keep systems reliable, performant, and straightforward to operate as they scale.
What You'll Do
Integrate AI products that process data from external sources and multiple systems in real time.
Route streaming responses and language model requests across providers, with fallback and cost controls.
Monitor latency, costs, and error rates, then address issues proactively before they degrade the experience.
Make architectural decisions that balance system quality with simple, maintainable designs.
Build application code alongside platform and operational work, and investigate production issues through instrumentation and root-cause analysis.
What We're Looking For
At least 3 years of production backend engineering experience, including substantial TypeScript experience and ownership of production systems.
Production experience with Docker and Kubernetes, plus solid knowledge of PostgreSQL, APIs, queues, and caching.
Strong system design skills and the ability to reason about performance, latency, reliability, and cost trade-offs.
Experience improving platform reliability and performance under production load, and building observability to diagnose complex systems.
Experience with streaming responses or language model request routing across providers is valuable.
Comfort contributing to frontend code when needed, and experience with CI/CD, safe deployments, and incident follow-up is beneficial.
Compensation & Benefits
Annual base salary: β¬60,000 to β¬90,000. Visa sponsorship is not available.
Location
Hybrid work arrangement, based in Munich, Germany.
Similar jobs
Search more Platform Engineer jobsBuild and evolve a self-service cloud platform that helps engineering teams deploy, monitor, and operate applications reliably, securely, and efficiently through automation, observability, and cloud-native practices.
Senior Platform Engineer - Container Services
Design, build, and operate Kubernetes-based container infrastructure across a global private cloud, improving automation and reliability while shaping platform modernization and multi-region resilience.
Design and operate production AI agents and cloud platform infrastructure, improving reliability and developer self-service through automation across Kubernetes, GitOps, CI/CD, and observability.
Design and operate production AI agents and cloud infrastructure that power a developer platform, reduce operational toil, and improve reliability through automation and self-service.
