Staff Engineer (Core & MLOps)

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.

• 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.