Compute Software Architect
Role Overview
The Software Architect, Compute Platform and Control Plane will be a senior individual contributor
responsible for shaping the architecture and technical direction of the core software systems that power the
Compute infrastructure platform.
This role will work across the compute platform and control plane, spanning provisioning, scheduling,
placement, lifecycle management, capacity orchestration, fleet management, service APIs, and the
foundational distributed systems that support large-scale cloud infrastructure.
The ideal candidate brings exceptional depth in software architecture, distributed systems, and cloud
infrastructure, with the ability to reason across complex systems, identify structural weaknesses, simplify
architectures, and define designs that can operate reliably at hyperscale.
This architect will work closely with senior engineers, engineering leaders, product teams, and adjacent
infrastructure organizations to evolve the compute platform to the next level of scalability, reliability,
efficiency, and engineering velocity.
Qualifications
Acknowledged expert/professional within company and/or industry nationally and internationally. Provides leadership in the development and strategic direction of new products, processes, techniques. Acts as primary consultant on large projects that effect the organization's long term objectives / strategy. BS or MS degree or equivalent experience relevant to functional area. 10 more years of software engineering or related experience.Responsibilities
Key Responsibilities
Compute Platform Architecture
Define and evolve the architecture of the core compute software platform. Establish clear architectural
principles, service boundaries, APIs, interfaces, and ownership models across compute platform
components.
Compute Control Plane Architecture
Provide deep technical leadership across compute provisioning, scheduling and placement, capacity
discovery and allocation, instance and host lifecycle management, configuration and state management,
fleet orchestration, health monitoring and remediation, failure recovery, service APIs, and regional isolation.
Distributed Systems Leadership
Serve as a technical authority for distributed systems design. Drive architectural rigor in consistency,
concurrency, state management, partitioning, replication, idempotency, failure recovery, dependency
management, and service isolation.
Cloud Infrastructure Architecture
Apply deep cloud infrastructure expertise to the design and evolution of the compute platform. Understand
the end-to-end lifecycle of cloud compute capacity, from resource discovery and orchestration through
provisioning, customer consumption, maintenance, failure recovery, and retirement.
Reliability and Resiliency
Embed reliability and resilience into the architecture of the platform. Design for fault containment, graceful
degradation, recovery, retry safety, deployment safety, and failure isolation.
Scalability and Performance
Identify scaling limitations across the compute platform and control plane. Develop architectures that
improve throughput, latency, efficiency, and resource consumption while reducing unnecessary
infrastructure overhead.
Platform Simplification and Modernization
Identify legacy complexity, duplicated services, and architectural patterns that limit engineering velocity or
operational efficiency. Define pragmatic modernization strategies that allow critical systems to evolve
without unnecessary disruption.
AI-Enabled Platform Transformation
Help drive the use of AI to advance both the compute platform and software engineering practices. Identify
opportunities to apply AI to software development, testing, code analysis, debugging, operational
diagnostics, incident analysis, anomaly detection, failure prediction, root-cause analysis, capacity
optimization, and automated remediation.
Technical Leadership and Influence
Operate as a senior technical leader across organizational boundaries. Lead complex architecture reviews,
drive alignment on critical technical decisions, mentor senior engineers, and partner with Distinguished
Engineers, Architects, Directors, and Vice Presidents on long-term platform strategy.
Expected Impact
- A simpler, more coherent compute platform architecture.
- A highly scalable and resilient compute control plane.
- Clearer service boundaries and stronger platform APIs.
- Reduced architectural fragmentation and technical debt.
- Improved reliability and fault isolation.
- Better scalability and performance across critical services.
- Faster engineering velocity through reusable platform capabilities.
- More effective use of AI to improve engineering and operational workflows.
• 12+ years of experience in software engineering, distributed systems, cloud infrastructure, or large-scale
platform development.
- Deep expertise in software architecture and distributed systems.
- Strong experience designing and operating large-scale, highly available services.
- Significant experience with cloud infrastructure or large-scale infrastructure platforms.
- Strong understanding of control-plane architecture, service APIs, state management, orchestration, and
- Experience designing systems for scalability, reliability, fault tolerance, and operational efficiency.
- Ability to reason across large and complex software systems and identify architectural simplifications.
- Proven ability to influence technical direction across multiple engineering teams and organizations.
- Strong programming and systems fundamentals.
- Experience designing cloud compute platforms or large-scale infrastructure control planes.
- Deep experience with scheduling, placement, provisioning, resource management, or fleet orchestration
- Experience operating systems across multiple regions and failure domains.
- Experience modernizing large-scale infrastructure software while maintaining production stability.
- Strong understanding of cloud infrastructure economics and the relationship between architecture,
• Experience applying AI-assisted development or AI-driven operational techniques in production
engineering environments.
• Experience working with GPU or accelerated compute infrastructure from a software platform
perspective.
• Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, or a related technical
discipline.
Technical Profile
The ideal candidate is a hands-on software architect with deep technical credibility and broad systems
perspective. They are comfortable going deep into distributed protocols, state machines, consistency
models, service interfaces, failure modes, and performance bottlenecks, while also reasoning about the
architecture of a very large cloud platform as a whole.
Most importantly, they will combine deep software architecture expertise with strong cloud infrastructure
judgment and the ability to influence the direction of critical compute systems across the organization.
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