Staff Software Engineer (Platform Infrastructure, Foundations)

Anyscale; San Francisco (CA); On-site; USD 150,000 - 200,000; Full time

Job summary

Deepstreamtech is seeking a Staff Software Engineer in San Francisco to lead the technical vision for our Infrastructure team. You will architect evolutionary control and data planes for scalable AI workloads and set Kubernetes standards while mentoring engineers. The ideal candidate has extensive experience in production code, cloud-native technologies, and advanced Linux networking expertise, ensuring reliability and system optimization. This role demands strong leadership in a fast-paced environment and direct influence on technical direction.

Qualifications

• 5+ years of experience writing high-quality production code.
• Expertise in cloud-native technologies and Kubernetes-based deployments.
• Advanced knowledge of Linux kernel and networking.

Responsibilities

• Lead the technical vision for the Infrastructure team.
• Architect the evolution of control plane and data plane.
• Set standards for Kubernetes-based cloud-native infrastructure.

Skills

Go

Python

Kubernetes

Cloud-native technologies (AWS, Azure, GCP)

Networking

Security

Observability stacks (Prometheus, Grafana)

Education

Bachelor's degree in Computer Science or Engineering

Job description

Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• 3+ years of experience writing high-quality production code
• Hands-on experience in building and maintaining highly available, scalable, and performant distributed system
• Expertise in cloud-native technologies (AWS, Azure, GCP) and Kubernetes-based deployments
• Deep understanding of networking, security, and authentication mechanisms in cloud environment
• Familiarity with observability stacks (Prometheus, Grafana etc)
• Proficiency in Go and Python
• Knowledge of low-level operating system foundations (Linux kernel, file systems, containers)
• Experience: 5+ years of experience writing high-quality production code and leading complex distributed systems projects
• Architectural Depth: Proven track record of designing and maintaining highly available, scalable, and secure cloud-native platforms (AWS, Azure, or GCP)
• Kubernetes Mastery: Deep expertise in Kubernetes-based deployments and container orchestration at massive scale
• System Foundations: Advanced knowledge of Linux kernel, networking, and low-level operating system foundations
• Technical Proficiency: Mastery of Go and Python, with the ability to set coding standards and best practices for the team
• Leadership Skills: Demonstrated ability to mentor senior engineers, influence technical direction without direct authority, and navigate complex trade-offs in a fast-paced environment

What the job involves

• Anyscale is seeking a Staff Software Engineer to lead the technical vision for our Infrastructure team
• As a Staff Engineer, you will be responsible for the architectural evolution of our control plane and data plane, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world
• You will act as a force multiplier, setting the standards for Kubernetes-based cloud-native infrastructure while mentoring engineers and driving cross-functional alignment across the Ray open-source community and our proprietary product teams
• Architectural Leadership: Define and drive the multi-year technical roadmap for services that orchestrate Ray clusters across diverse cloud and on-premises environments
• Systemic Optimization: Lead the design and optimization of high-performance control plane components specifically tailored for large-scale, heterogeneous AI/ML workloads
• Platform Reliability: Establish the organization-wide standards for the reliability, scalability, and observability of Anyscale-managed infrastructure
• Strategic Integration: Direct the long-term strategy for accelerator integration (GPUs, TPUs) and container management to ensure seamless execution of distributed workloads
• Technical Governance: Lead complex design and architecture discussions, resolving deep technical debt and ensuring engineering excellence across the organization
• Cross-Functional Influence: Partner with ML experts and customer-facing teams to translate market needs into robust infrastructure foundations