Software-Engineer, Platform-Engineer, Infrastructure-Engineer Jobs

Join a team of engineers at NVIDIA dedicated to scaling the AI infrastructure that powers cutting-edge data science applications. Our team solves complex challenges across datacenter hardware, networking, distributed systems, and software deployment. We collaborate closely to design and deliver leading infrastructure solutions. We value strong technical foundations paired with creative thinking and a bias toward execution. Together, we continuously push boundaries, grow our skills, and advance NVIDIA’s capacity to build and deploy AI-based infrastructure at scale.

What you will be doing:

• Contribute to a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers.
• Build end-to-end automation of data center management, break/fix, and the full span of system upkeep for large-scale Machine Learning systems.
• Implement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets.
• Harness multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.
• Build automated test infrastructure that we use to qualify distributed systems for operation.
• Partner with engineering teams across NVIDIA to ensure the software integrates seamlessly from the hardware all the way up to the AI training applications.

What we need to see:

• 12+ years of experience in a similar role working on large-scale production systems.
• BS in Computer Science/Engineering/Physics/Mathematics or other comparable degree, or equivalent experience.
• Expert level knowledge of a systems programming language (Go, Python, and/or Rust) and a solid understanding of Data Structures and Algorithms.
• Strong background in Linux system administration and management.
• Deep knowledge of container orchestration platforms such as Kubernetes and/or SLURM.
• Understanding of performance, security, and reliability in complex distributed systems.
• Familiarity with system level architecture, data synchronization, fault tolerance, and state management.

Ways to stand out from the crowd:

• Proficiency in designing and building widespread distributed networks.
• Experience managing large-scale distributed systems independently of cloud providers.
• Extensive expertise in datacenter operations and GPU hardware.
• Hands-on experience working with RDMA networking.
• Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, SLURM).

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

Originally posted on Himalayas

Affirm's engineering team is building a large-scale, highly-available, and global infrastructure that is shared across multiple financial products. Ensuring that our infrastructure is accessible to all engineers is critical to the success of the business. We pride ourselves on our culture across engineering of engaging in thorough technical design review, operational excellence, and capable incident response and analysis.

The Compute Platform team owns the EKS foundation that Affirm's products run on, from cluster provisioning and lifecycle through the safety standards that keep thousands of workloads reliable at scale. Affirm operates 90+ EKS clusters across environments and regions, and this team is responsible for making that fleet standardized, automated, observable, and self-healing, while establishing and enforcing the workload configuration standards that protect availability. Our mission is to provide a secure, reliable, and scalable Kubernetes platform that lets infrastructure and application teams deploy and operate with confidence and minimal operational friction.

What you’ll do

As a member of the Compute Platform organization, you will collaborate with other teams - including Product, Infrastructure, Traffic, Cost & Capacity Engineering to:

• Architect and evolve Affirm's EKS platform, driving strategy across cluster lifecycle, node management, and shared cluster components

• Lead the technical direction for cluster provisioning, upgrades, and teardown through standardized IaC (Terraform, Spacelift) and self-service workflows

• Own the reliability of core shared components across the fleet (Karpenter, CoreDNS, VPC CNI, Kube Proxy, Metrics Server, etc) and the CI/CD pipeline that ships them consistently

• Define and enforce EKS workload safety standards covering resource configuration, workload isolation and blast radius, disruption tolerance (PDBs), Karpenter consolidation strategies, etc

• Build the enforcement and automation path that moves each standard from research and white-glove onboarding through broad adoption to policy-enforced defaults for new workloads

• Establish the observability, baseline audits, and reporting needed to identify hot spots and measure risk mitigation over time

• Partner with cluster-user teams (checkout, batch, ML, analytics, DevProd, etc) to understand workload needs and shape the platform accordingly

• Drive cost and capacity strategy across node scaling, bin packing, and EC2 instance selection

• Mentor engineers across the Compute Platform teams and set the bar for operational excellence

• Participate in the on-call rotation, triage and catalogue runtime K8s issues, and collaborate with SRE on production incidents

What we look for

• Deep EKS and Kubernetes internals expertise, including cluster upgrades, node lifecycle, scheduling, and autoscaling (Karpenter, Cluster Autoscaler)

• Demonstrated experience automating Kubernetes operations at fleet scale, from cluster provisioning, upgrades, and node lifecycle to self-healing remediation and policy-driven enforcement, replacing manual toil with auditable, self-service workflows

• Strong grasp of workload reliability patterns: resource tuning, probes, PDBs, topology and isolation constraints

• Experience designing and enforcing platform standards through policy (admission control, OPA/Gatekeeper or equivalent) and automated frameworks

• Infrastructure as Code fluency with Terraform and a GitOps or pipeline-driven delivery model (ArgoCD, kube-applier, or similar)

• Observability instincts: defining SLOs, building metrics, logs, and alerting coverage, and running data-driven baseline audits

• Cross-functional collaboration skills with platform, product, SRE, and capacity teams

• Demonstrated mentorship and technical leadership across teams

• Drive to track emerging Kubernetes community best practices and adapt them to Affirm's needs

Qualifications

• 10+ years in software or infrastructure engineering with proven delivery of complex platform solutions

• 6+ years hands-on operating production Kubernetes at scale, ideally EKS on AWS

• Strong cloud-native architecture experience on AWS (EC2, VPC, IAM, EKS)

• Experience with Infrastructure-as-Code (Terraform, Spacelift a plus) and GitOps-style deployment pipelines

• Expert-level proficiency in Go or Python and a proven track record building production-grade Kubernetes controllers, operators, and platform tooling that other engineering teams depend on

• Track record designing and enforcing standards across many teams without becoming a bottleneck

• Exceptional problem-solving and systems-thinking skills

• Demonstrated leadership and cross-functional influence

• This position requires either equivalent practical experience or a Bachelor’s degree in a related field.

Base Pay Grade - R

Equity Grade - 15

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

USA base pay range (CA, WA, NY, NJ, CT) per year: $265,000 - $325,000

USA base pay range (all other U.S. states) per year: $236,000 - $296,000

Originally posted on Himalayas

About the Role

Abnormal AI empowers businesses of all sizes to combat cybercrime through our innovative cloud products. To achieve our mission, we're building a suite of interconnected security solutions on a unified platform, designed to operate flawlessly in global data centers.

The Development Infrastructure team plays a critical role in multiplying the impact of our product teams. We create an environment that fosters high-quality software development, and engineering excellence. This team has become instrumental in the success of our engineering organization.

You are someone who:

• Thrives in a collaborative, fast-paced environment
• Possesses a passion for helping others build world-class systems
• Demonstrates exceptional teamwork skills
• Embraces continuous learning and enjoys tackling complex problems

What you will do

• Lead the design and delivery of complex, multi-component features and systems of the Development Infrastructure team's offerings, and shape the roadmap for this area.
• Develop and maintain CI/CD infrastructure and tools for Engineering to develop and ship their changes reliably with less effort.
• Design and implement enhancements to GHA infrastructure, base Docker images and build/deploy pipelines with improvements in scalability, performance and costs.
• Use AI tools to explore and compare solutions, and adapt the generated changes to real production constraints, weighing system complexity and long-term maintainability.
• Take ownership of on-call issues, including complex issues where the root cause is unclear, and fix the systemic gaps behind them.
• Participate in planning, code reviews, standups, and other aspects of the software development life cycle, and coach other engineers on the team.

Must Haves

• 3+ years of professional experience as a hands-on engineer building backend systems and/or platforms.
• 2+ years of experience working with Python.
• Experience delivering complex projects end-to-end in a cloud native environment.
• Experience building or operating CI/CD, build, or deployment systems in production, including on-call and incident response.
• Understanding of distributed systems, containerization and microservices.
• Practical experience using Generative AI tools in day-to-day engineering workflows.

Nice to Haves

• Experience creating and maintaining CI/CD systems.
• Experience with GitHub Actions.
• Experience with Go.
• Experience with Bazel.
• Experience working on or with teams like “Engineering Effectiveness”, “Engineering Productivity”, “Development Experience”, “Development Infrastructure” or similar.
• Knowledge of Docker, Kubernetes, or similar technologies.
• Familiarity with Generative AI tools such as Codex and Claude, and experience driving AI-first workflows and solutions.

Originally posted on Himalayas

Location: Remote — U.S.

Employment: Full-time
Experience: 5+ years
Compensation: $170,000–$230,000 + equity

About the Role

We're looking for an experienced Senior Software Engineer, Platform to help design and build the infrastructure behind a fast-growing software product.

This is a hands-on engineering role with significant ownership across platform architecture, cloud infrastructure, distributed systems, developer tooling, and data pipelines.

You'll help define how services run in production, build infrastructure that other engineers rely on, and make architectural decisions around scalability, reliability, security, and developer experience.

The ideal candidate combines deep infrastructure expertise with strong software engineering fundamentals and enjoys building in an early-stage environment where there is significant room to shape the platform.

What You'll Do

• Design, build, and operate scalable production infrastructure.
• Build and improve distributed systems and high-availability services.
• Develop data pipelines for ingesting, processing, and storing production data at scale.
• Build and maintain cloud infrastructure and deployment systems.
• Improve CI/CD, developer tooling, and local development environments.
• Own observability across metrics, alerting, logging, and distributed tracing.
• Improve platform reliability, performance, and security.
• Build infrastructure-as-code and automation to make systems easier to operate and scale.
• Partner with product and engineering teams on architecture and technical decisions.
• Take broad ownership of platform initiatives from design through production.

What We're Looking For

• 5+ years of experience in platform, infrastructure, backend, or distributed systems engineering.
• Strong production experience with Go.
• Deep experience with Kubernetes and containerized production environments.
• Strong cloud infrastructure experience with GCP, AWS, or Azure.
• Experience with Terraform or other infrastructure-as-code tooling.
• Strong understanding of distributed systems, networking, storage, and production reliability.
• Experience building or operating production data pipelines.
• Hands-on experience with CI/CD and observability systems.
• Strong software engineering and system-design fundamentals.
• High ownership and ability to operate independently in an early-stage environment.

Strong Plus

• Experience building internal developer platforms or infrastructure used by other engineers.
• PostgreSQL or other production database experience.
• Security-focused infrastructure experience.
• Authentication, authorization, or access-control systems.
• Experience operating highly available enterprise software.
• Experience joining an early-stage startup and building foundational infrastructure from scratch.

Originally posted on Himalayas

About the Role

Abnormal AI empowers businesses of all sizes to combat cybercrime through our innovative cloud products. To achieve our mission, we're building a suite of interconnected security solutions on a unified platform, designed to operate flawlessly in global data centers.

The Development Infrastructure team plays a critical role in multiplying the impact of our product teams. We create an environment that fosters high-quality software development, and engineering excellence. This team has become instrumental in the success of our engineering organization.

You are someone who:

• Thrives in a collaborative, fast-paced environment
• Possesses a passion for helping others build world-class systems
• Demonstrates exceptional teamwork skills
• Embraces continuous learning and enjoys tackling complex problems

What you will do

• Lead the design and delivery of complex, multi-component features and systems of the Development Infrastructure team's offerings, and shape the roadmap for this area.
• Develop and maintain CI/CD infrastructure and tools for Engineering to develop and ship their changes reliably with less effort.
• Design and implement enhancements to GHA infrastructure, base Docker images and build/deploy pipelines with improvements in scalability, performance and costs.
• Use AI tools to explore and compare solutions, and adapt the generated changes to real production constraints, weighing system complexity and long-term maintainability.
• Take ownership of on-call issues, including complex issues where the root cause is unclear, and fix the systemic gaps behind them.
• Participate in planning, code reviews, standups, and other aspects of the software development life cycle, and coach other engineers on the team.

Must Haves

• 3+ years of professional experience as a hands-on engineer building backend systems and/or platforms.
• 2+ years of experience working with Python.
• Experience delivering complex projects end-to-end in a cloud native environment.
• Experience building or operating CI/CD, build, or deployment systems in production, including on-call and incident response.
• Understanding of distributed systems, containerization and microservices.
• Practical experience using Generative AI tools in day-to-day engineering workflows.

Nice to Haves

• Experience creating and maintaining CI/CD systems.
• Experience with GitHub Actions.
• Experience with Go.
• Experience with Bazel.
• Experience working on or with teams like “Engineering Effectiveness”, “Engineering Productivity”, “Development Experience”, “Development Infrastructure” or similar.
• Knowledge of Docker, Kubernetes, or similar technologies.
• Familiarity with Generative AI tools such as Codex and Claude, and experience driving AI-first workflows and solutions.

Originally posted on Himalayas