Staff DevOps Engineer

Who you are

• BS/MS/PhD degree in Computer Science, Software Engineering, or a related technical field
• 5+ years of professional software engineering experience with a heavy focus on backend systems, distributed architectures, and infrastructure management
• Strong proficiency in Java, Python and/or Rust, with a solid grasp of writing high-performance, concurrent backend code
• Production experience with stream-processing frameworks, specifically Apache Flink
• Experience setting up observability stacks (eg Grafana, Prometheus, ELK, etc.)
• Solid experience with containerization and orchestration (Docker, Kubernetes), including configuring network policies, storage, and auto-scaling
• Deep experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools such as OpenTofu/Terraform and Ansible
• Hands-on experience with modern GitOps practices (e.g., Argo CD) and managing CI/CD automation pipelines
• Solid experience with relational databases (e.g., PostgreSQL), in-memory datastores (e.g., Valkey/Redis), and high-throughput data storage strategies
• Able to scale yourself with AI coding assistants while still fully understanding and taking absolute ownership of all code and infrastructure configurations you commit
• Excellent communication skills, with a proven ability to design resilient architectures and explain complex infrastructure paradigms to the broader team
• Deep experience with Apache Pulsar (or Kafka) handling high-throughput, event-driven streaming architectures
• Rust experience with async runtimes (Tokio) and message-driven architectures
• Experience architecting real-time media pipelines using WebRTC (LiveKit, RealtimeKit) with a focus on server-side jitter buffering and network impairment handling
• Deep understanding of audio codecs, specifically optimizing server-side Opus encoding/decoding for CPU efficiency and low-latency distribution
• Familiarity with MLOps frameworks, GPU orchestration in Kubernetes, and serving LLMs at scale
• Background in high-availability, real-time systems, telecommunications, or safety-critical networks
• Prior experience or a deep interest in aerospace, aviation, or autonomous tracking systems

What the job involves

• As a Staff DevOps Engineer, you will architect, develop, and scale the core services, real-time data pipelines, and distributed infrastructure that power our cutting-edge AI products. You will bridge the gap between complex AI models and production-ready systems, ensuring that our high-throughput, real-time data streaming environment is reliable, secure, and infinitely scalable
• Architect and maintain highly available backend systems, distributed data pipelines, and scalable cloud infrastructure to support real-time AI applications
• Leverage infrastructure-as-code (IaC) and cloud-native tooling to build, manage, and optimize our production, staging, and development environments
• Build and manage stream-processing jobs capable of handling global, high-frequency data streams with ultra-low latency
• Work cross-functionally with AI Research, Engineering, and Data Science teams to containerize, deploy, orchestrate, and monitor scalable ML models and infrastructure
• Own the full development lifecycle—from system design and infrastructure provisioning to deployment, proactive monitoring, and capacity planning
• Maximize system performance, observability, and reliability; respond to high-priority production issues with advanced debugging, root cause analysis, and blameless post-mortems
• Mentor and guide team members, fostering an engineering culture centered around DevOps practices, automation, and distributed systems best practices