Senior Software Engineer
NVIDIA is hiring a Senior Software Engineer in Bengaluru, India. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Level rates this software engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include LangChain, LlamaIndex and AutoGen.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
Build distributed software platforms for enterprise observability, automation, and AI-driven reliability operations.
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.
How we rate this
Senior Software Engineer at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where observability was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Distributed Systems, Observability, Infrastructure, and Automation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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