Staff Engineer (Core & MLOps)

Jobgether SRL; Schweiz; Remote; CHF 140.000 - 200.000; Vollzeit

Benefits dieser Stelle

Fully remote

Flexible hours

Global engineering community

Zusammenfassung

Jobgether SRL is seeking a Staff Engineer (Core & MLOps) based in Switzerland to shape foundational infrastructure for large-scale web data products. You will own architecture for control planes, enable AI-driven workflows, and drive reliability across multi-cloud environments using Kubernetes, Kafka, Java, Python, and gRPC.

You will lead multi‑cluster routing, deployment pipelines, and service contracts, while mentoring engineers and setting platform standards in a globally distributed,

Qualifikationen

• 10+ years building scalable distributed backend systems.
• Advanced Java with reactive frameworks and Python proficiency.
• Deep experience with gRPC and Protocol Buffers.
• Hands-on Kubernetes, Terraform, Kafka at scale.
• Experience designing telemetry pipelines and reliability practices.
• Strong writing and cross-team communication.

Aufgaben

• Architect and evolve core control and context planes for scalable services.
• Own service chassis, multi-language client libraries, and deployment pipelines.
• Define inter-service contracts and API gateway standards.
• Operate core platform infra including Kubernetes, Kafka, and real-time pipelines.
• Lead architectural strategy through RFDs and platform initiatives.
• Establish reliability engineering practices and incident post-mortems.
• Mentor engineers and drive consistent engineering practices across teams.

Kenntnisse

Java

Python

Kubernetes

gRPC

Protocol Buffers

Terraform

Kafka

MLOps

Software architecture

Tools

Helm

CI/CD pipelines

Jobbeschreibung

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Engineer (Core & MLOps) based in Switzerland.

This role offers the opportunity to shape foundational infrastructure powering large-scale web data products and distributed engineering teams. You’ll own the architecture of core control and context planes that enable services and AI-driven workflows to operate reliably and efficiently. Working across Kubernetes, Kafka, Java, Python, gRPC, and multi-cloud infrastructure, you’ll tackle complex distributed systems challenges at production scale. You’ll establish engineering standards, reliability practices, and service contracts that influence multiple product squads. The role combines hands‑on architecture with technical leadership, mentoring, and cross‑functional alignment. In a globally distributed, remote‑first environment, you’ll have significant autonomy to solve challenging infrastructure problems and influence long‑term platform strategy.

• Architect and evolve the control and context planes, advancing service and schema registries, SLO enforcement, health‑aware routing, automated canary releases, and operational feedback loops.
• Own the service chassis and golden path, maintaining and improving multi‑language Java and Python client libraries, standardized workload specifications, Helm charts, and deployment pipelines.
• Define and govern inter‑service contracts, including gRPC and Protocol Buffer definitions, API gateway transcoding, versioning policies, and schema evolution standards.
• Operate and improve the core platform infrastructure across Kubernetes, Terraform, HAProxy/Nginx, Confluent Kafka, real‑time billing pipelines, Valkey, and database modernization initiatives.
• Lead architectural strategy through Requests for Discussion (RFDs) covering workflow orchestration, gateway orchestration, multi‑cluster routing, automated failover, and other critical platform initiatives.
• Establish reliability engineering practices, including SLOs, SLIs, error budgets, fault isolation, and automated weighted canary deployments.
• Participate in shared infrastructure on‑call rotations, lead incident post‑mortems, and convert operational insights into platform improvements.
• Mentor engineers across multiple squads, review architectural proposals, and establish engineering practices that make reliable software development more consistent and efficient.

Requirements

• 10+ years of experience building scalable distributed backend systems, with a strong track record of creating internal platforms or core libraries adopted across engineering organizations.
• Advanced Java expertise, including reactive frameworks such as Vert.x or Netty, combined with strong Python proficiency.
• Deep experience with gRPC and Protocol Buffers, including schema evolution and backward compatibility in mission‑critical systems.
• Hands‑on production experience with Kubernetes at scale, Terraform, and event‑streaming platforms such as Kafka.
• Experience designing automated telemetry pipelines, materialized views, feature stores, or other feedback systems that use production data to dynamically improve system behavior.
• Strong reliability engineering background, including SLO/SLI definition, blast‑radius analysis, fault tolerance, and rigorous service contracts.
• Exceptional technical writing skills and the ability to communicate complex architectural concepts clearly while driving alignment across teams.
• Strong written and interpersonal communication skills suited to a globally distributed, remote‑first environment.
• A curious, continuous‑learning mindset with an interest in evaluating new technologies, architectures, and engineering approaches.
• Experience with Temporal, DBOS, or similar durable execution platforms is a plus.
• MLOps experience, including model serving, performance monitoring, or production drift detection, is advantageous.
• Familiarity with zero‑trust networking and service meshes such as SPIRE, mTLS, Cilium, Istio, or Envoy is beneficial.
• Experience building developer tooling such as CLIs, SDKs, or project generators is a plus.
• Experience with large‑scale web scraping or crawling, or contributions to distributed‑systems and data‑extraction open‑source projects, is advantageous.

Benefits

• Fully remote, remote‑first working environment with flexible working hours.
• Freedom and flexibility to work from the location where you are most productive.
• Opportunity to work on core infrastructure supporting large‑scale web data pipelines and distributed systems.
• Exposure to cutting‑edge open‑source technologies, tools, and evolving AI and web data infrastructure.
• Opportunities to attend conferences and connect with colleagues across the globe.
• Collaboration with a diverse, multicultural, and globally distributed engineering community.
• High level of autonomy and organizational trust.
• Opportunities to influence platform architecture, engineering standards, and technical strategy across multiple teams.