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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, AIOps and Observability - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $200,000.0 - $322,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Big Data, C Sharp (Programming Language), Software as a Service, Computer Engineering, Data Centers, Software Debugging, Distributed Systems, Python (Programming Language), Machine Learning, Network Monitoring, Prometheus, Datadog, Large Language Models, Grafana, Generative AI, Containerization, Kubernetes, Apache Kafka, Machine Learning Operations, Vertica, Virtual Agents, Data Pipelines, Docker, Pagerduty, Golang, Programming Languages, Microservices - **Published:** August 2, 2026 - **Apply:** https://www.disabledperson.com/jobs/73962407-senior-software-engineer-aiops-and-observability ## About the Role * Bachelor's degree in computer science and engineering, or related field, or equivalent experience. * 12+ years of experience in product development and full stack engineering, with 5+ years of experience in developing and operating observability platforms and solutions, preferably in a cloud-native environment. * Strong knowledge and experience with observability tools, such as Prometheus, Victoria Metrics, Vector, Loki, Grafana, Alert Manager, Clickhouse, OpenTelemetry, etc. * Hands-on knowledge in AIOps tools such as BigPanda, PagerDuty, Datadog, etc. * Experience with Kubernetes, Nomad, Docker, and microservices architectures as well as experience with streaming services to ingest billions of events using NATS, Kafka, etc * Proficient in one or more programming languages, such as Go, Python, Java, C#, etc. * Passionate about observability and delivering high-quality internal platforms. * Experience with developing Observability solutions to monitor On-prem and Public Cloud environments. * Experience with running large Observability platforms on BareMetal Infrastructure * Establish scalable data pipelines and instrumentation for collecting, aggregating, and visualizing telemetry and operational metrics. Ways To Stand Out From The Crowd: * Deep understanding of implementing Observability solutions to large scale on-prem Infrastructure and Networking. * Hands-on experience with managing large scale Observability Platforms with LLMs & ML Models and building custom services to ingest billions of metrics and logs from wide range of assets. * Developed unified cloud observability platform to monitor Network, Compute, Power, Storage, Operating Systems, Security, Applications, SaaS Platforms. * Demonstrated experience and expertise in using machine learning and Generative AI to develop solutions such as predictive monitoring, incident diagnosis, summarization and correlation. * Demonstrate proficiency in AI/ML systems, generative AI, or agentic AI frameworks. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, self-motivated and enjoy having fun, then what are you waiting for apply today! ## Description We are looking for a highly skilled Senior Software Engineer to design and develop AIOps & Observability platforms at NVIDIA. The platforms are used by internal teams to monitor, diagnose, and optimize the products, millions of assets and services in cloud, on-prem, data centers, supply chain, and edge. You will work with a team of engineers, product managers, and partners to define the observability strategy, roadmap, and standard methodologies for NVIDIA. You will also mentor and coach other engineers on observability, machine learning, tools and techniques. What you will be doing: * Lead the design, development, and deployment of AIOps & Observability platforms, including metrics, logs, traces, events, alerts, dashboards, and visualizations. * Drive the technical vision and roadmap for AIOps and Observability initiatives, aligning with business goals and industry best practices. * Collaborate with other teams and customers to understand their observability needs and provide solutions that meet their requirements and expectations. * Establish and implement observability standards, guidelines, and processes across NVIDIA. Research, evaluate, and adopt new observability technologies and frameworks that can enhance user experience. * Provide peer reviews to other engineers including feedback on performance, scalability, security and correctness. * Work with Data scientists to implement machine learning models for anomaly detection, forecasting, and root cause analysis on logs, metrics, and events. Handle large volumes of data and ensure data quality, security, and compliance. * Develop and operate scalable, reliable, and distributed systems that can handle high traffic and complex workloads. * Develop AI agents and AI-native observability tools that help engineers detect, understand, and resolve production issues faster. Build agentic workflows that reason across logs, metrics, traces, events, alerts, topology, and incident history to support anomaly detection, forecasting, root cause analysis, automated debugging, and remediation recommendations. ## Related Videos - [LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices](https://www.wearedevelopers.com/videos/1582-llmops-driven-fine-tuning-evaluation-and-inference-with-nvidia-nim-nemo-microservices) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Retooling and refactoring - an investment in people.](https://www.wearedevelopers.com/videos/371-retooling-and-refactoring-an-investment-in-people) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)