We are seeking a Senior Software Engineer with strong infrastructure expertise to design, build, and operate the next generation of our enterprise Observability, Automation, and AI-driven Reliability Platform.
This role will build highly scalable distributed systems and platform services spanning Storage, Compute, Network, VMware, OpenShift, and bare-metal infrastructure. The engineer will help transform infrastructure operations from reactive monitoring and manual remediation to proactive, predictive, and AI-driven autonomous operations.
What You Will Be Doing:
Design, build, and operate distributed software platforms for enterprise observability, telemetry, automation, and infrastructure reliability at large scale.
Develop reusable platform services, APIs, automation frameworks, and control planes that enable self-service, reduce operational toil, and automate infrastructure operations across multiple engineering teams.
Build scalable telemetry and event-processing systems spanning metrics, logs, traces, events, topology, and alerts, with the performance and efficiency to process billions of infrastructure signals.
Build intelligent and AI-native reliability capabilities, including agentic workflows for anomaly detection, forecasting, root-cause analysis, automated debugging, and closed-loop remediation.
Drive technical architecture and engineering direction across Storage, Compute, Network, and Platform domains, solving complex and ambiguous problems that span multiple teams.
Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness.
Provide technical leadership and mentorship, influence engineering standards and architecture decisions, and deliver measurable improvements in reliability, MTTR, operational toil, engineering productivity, and infrastructure efficiency.
What We Need To See:
Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience, with 10+ years of software engineering, SRE, infrastructure, or distributed-systems experience and demonstrated technical leadership.
Strong software engineering expertise in Go, Python, or equivalent languages, with experience designing and building production-grade distributed systems, platform services, APIs, and automation.
Proven experience owning complex software/platform initiatives across multiple teams or infrastructure domains, from architecture and implementation through adoption and measurable impact.
Deep understanding of distributed systems, event-driven architectures, microservices, APIs, and high-throughput data processing, including technologies such as Kafka, NATS, gRPC, or equivalent.
Strong experience with modern observability and telemetry platforms, including OpenTelemetry, Prometheus, VictoriaMetrics, Vector, Loki, Grafana, ClickHouse, or equivalent technologies.
Strong SRE and infrastructure knowledge across Kubernetes/OpenShift, VMware, bare-metal, storage, networking, and/or cloud environments, with experience using Terraform, Ansible, or equivalent automation technologies.
Demonstrated ability to solve ambiguous problems, influence technical direction without direct authority, mentor engineers, establish engineering standards, and deliver measurable operational and business outcomes.
Ways To Stand Out From The Crowd:
Experience building software and reliability platforms for large-scale on-premises infrastructure, particularly Storage, Compute, Networking, VMware, and Kubernetes/OpenShift.
Deep understanding of storage and infrastructure telemetry, including IOPS, latency, NVMe health, SAN/NAS topology, block/object storage, and infrastructure failure domains.
Experience building self-healing systems, automated remediation, predictive operations, or autonomous SRE capabilities.
Production experience applying Generative AI, AIOps, LLMs, or Agentic AI to incident triage, RCA, operational intelligence, debugging, or remediation; experience with LangChain, LlamaIndex, AutoGen, or equivalent is a plus.
Experience building high-performance platform services using FastAPI, gRPC, or equivalent technologies.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
- 10+ years of software engineering, SRE, infrastructure, or distributed-systems experience
- Demonstrated technical leadership
- Strong software engineering expertise in Go, Python, or equivalent languages
- Experience designing and building production-grade distributed systems, platform services, APIs, and automation
- Experience owning complex software or platform initiatives across multiple teams or infrastructure domains
- Deep understanding of distributed systems, event-driven architectures, microservices, APIs, and high-throughput data processing
- Experience with Kafka, NATS, gRPC, or equivalent technologies
- Experience with modern observability and telemetry platforms
- SRE and infrastructure knowledge across Kubernetes/OpenShift, VMware, bare-metal, storage, networking, or cloud environments
- Experience using Terraform, Ansible, or equivalent automation technologies
- Ability to solve ambiguous problems, influence technical direction, mentor engineers, establish standards, and deliver measurable outcomes
- Experience building software and reliability platforms for large-scale on-premises infrastructure
- Deep understanding of storage and infrastructure telemetry, including IOPS, latency, NVMe health, SAN/NAS topology, block/object storage, and failure domains
- Experience building self-healing systems, automated remediation, predictive operations, or autonomous SRE capabilities
- Production experience applying Generative AI, AIOps, LLMs, or Agentic AI to operations
- Experience with LangChain, LlamaIndex, AutoGen, or equivalent
- Experience building high-performance platform services using FastAPI, gRPC, or equivalent technologies
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
