Senior Software Engineer (Serverless)

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer (Serverless) based in Switzerland.**

This role offers the opportunity to build the next generation of AI cloud infrastructure powering advanced machine learning workloads worldwide. You will work on a high-impact serverless platform designed to help developers deploy and scale AI applications without managing complex infrastructure. As a senior engineer, you will take ownership of critical distributed systems challenges, from GPU scheduling and runtime performance to customer-facing APIs and platform reliability. Working in a highly technical environment, you will influence architecture decisions, mentor engineers, and help define engineering standards. This position is ideal for an experienced software engineer passionate about large-scale systems, cloud technologies, and solving complex infrastructure challenges at the forefront of AI innovation.

### Accountabilities

• Design, develop, and maintain core components of a GPU-native serverless AI platform, including control planes, schedulers, runtimes, autoscaling systems, and customer-facing APIs.
• Solve complex engineering challenges related to cold-start optimization, GPU scheduling, multi-tenant isolation, fair resource allocation, request routing, and platform scalability.
• Own technical architecture decisions for key platform areas by creating design documents, evaluating solutions, and aligning engineering teams around effective approaches.
• Establish and maintain high engineering standards through code reviews, design reviews, technical guidance, and active collaboration with team members.
• Operate services with an SRE mindset by defining reliability objectives, improving observability, supporting incident response, and driving continuous platform improvements.
• Collaborate directly with customers on architecture discussions, performance optimization, and complex production issues requiring deep technical expertise.
• Partner with product, infrastructure, and go-to-market teams to translate customer needs into scalable technical roadmaps.
• Contribute to improving platform performance, reliability, and developer experience through innovative engineering solutions.
• Support knowledge sharing and technical mentorship to help raise the overall engineering capability of the team.

## **Requirements**

• 7+ years of professional software engineering experience with a proven track record of building and operating large-scale distributed systems.
• Strong programming experience with Golang, or the ability and willingness to quickly become proficient in the language.
• Deep experience with Kubernetes and container orchestration systems, including real-world operation of production environments.
• Strong understanding of distributed systems concepts such as consistency, availability trade-offs, queueing, backpressure, retries, idempotency, and multi-tenancy.
• Experience designing and operating high-throughput, low-latency services with a strong focus on performance optimization and reliability.
• Proven ability to take ownership of complex technical challenges, lead design discussions, unblock teams, and deliver impactful solutions.
• Strong software engineering fundamentals with the ability to write reliable, maintainable code and investigate complex technical problems.
• Collaborative mindset with excellent communication skills and the ability to work effectively across engineering and business teams.
• Experience with serverless platforms or function-as-a-service technologies such as Knative, AWS Lambda, GCP Cloud Run, Cloudflare Workers, or similar solutions is a strong advantage.
• Familiarity with GPU scheduling technologies, including Kubernetes device plugins, MIG, MPS, time-slicing, or NVIDIA GPU Operator, is highly desirable.
• Experience with ML inference technologies such as vLLM, TensorRT-LLM, Triton Inference Server, SGLang, or similar platforms is a plus.
• Knowledge of runtime optimization techniques including cold-start reduction, image streaming, checkpoint/restore, or sandboxing technologies is beneficial.
• Experience developing Kubernetes operators using Go and frameworks such as controller-runtime or kubebuilder is advantageous.
• Contributions to open-source projects related to serverless infrastructure, scheduling, or AI inference are a plus.

## **Benefits**

• Competitive compensation package.
• Flexible working environment with hybrid opportunities.
• High level of ownership and autonomy over technical decisions.
• Career development opportunities and continuous learning support.
• Opportunity to work on impactful AI infrastructure projects shaping the future of machine learning.
• Collaborative and innovative culture with highly skilled international teams.
• Exposure to cutting-edge technologies across cloud infrastructure, distributed systems, GPUs, and AI workloads.
• Opportunity to contribute to ambitious projects in a fast-moving, high-growth environment.