Staff Engineer — Core Platform & MLOps (Remote)

Lever, Inc.; Germany (OH); Remote; USD 136,000 - 204,000; Full time

Benefits offered by this job

Fully remote

Remote-first culture

Flexible hours

Global collaboration

Conference opportunities

Autonomy

Influence platform architecture

Job summary

Lever, Inc. is partnering to hire a Staff Engineer (Core & MLOps) based in Germany. You will shape foundational infrastructure powering large-scale web data products and distributed engineering teams, owning the architecture of core control and context planes for services and AI-driven workflows.

You'll work across Kubernetes, Kafka, Java, Python, gRPC, and multi-cloud infrastructure, establish reliability standards, mentor engineers, and influence platform strategy in a remote-first environment.

Qualifications

• 10+ years building scalable distributed backend systems.
• Advanced Java and Python proficiency.
• Deep experience with gRPC and Protocol Buffers.
• Kubernetes at scale, Terraform and Kafka experience.
• Strong reliability engineering background and service contracts.
• Excellent written and verbal communication for a remote-first org.

Responsibilities

• Architect and evolve control and context planes for services.
• Own the service chassis, libraries, Helm charts, and pipelines.
• Define inter-service contracts and API gateway standards.
• Operate core platform infra across Kubernetes, Terraform, Kafka.
• Lead architectural strategy via RFDs for orchestration and routing.
• Establish SLOs/SLIs, fault isolation, automated canary deployments.
• Participate in on-call rotations and post-mortems.
• Mentor engineers and drive alignment across squads.

Skills

Technical leadership

Communication

Mentoring

Problem solving

Tools

Kubernetes

Terraform

Kafka

gRPC

Protocol Buffers

Java

Python

Helm

Envoy

SPIRE

mTLS

Job description

Lever, Inc. is partnering to hire a Staff Engineer (Core & MLOps) based in Germany. You will shape foundational infrastructure powering large-scale web data products and distributed engineering teams, owning the architecture of core control and context planes for services and AI-driven workflows.

You'll work across Kubernetes, Kafka, Java, Python, gRPC, and multi-cloud infrastructure, establish reliability standards, mentor engineers, and influence platform strategy in a remote-first environment.