Senior Observability Engineer

Keysight Technologies, Inc.; Gurugram District; On-site; INR 3,800,000 - 7,000,000; Full time

Job summary

Keysight Technologies seeks a Senior Observability Engineer to design, implement, and continuously improve monitoring across on-premise infrastructure, VMs, Kubernetes, and bare-metal servers. You will shape observability strategy, establish SLIs/SLOs, and drive reliability through scalable architectures.

You will build and maintain pipelines with Zabbix, Splunk, Prometheus, and Grafana, and explore agentic AI to enhance triage and remediation with human-in-the-loop oversight.

Qualifications

• 5+ years in infrastructure or observability engineering in enterprise environments.
• Hands-on production experience with Zabbix and Splunk.
• Experience monitoring on-prem servers, virtualization, and Kubernetes clusters.
• Strong knowledge of compute, OS, networking, and storage layers.
• Experience applying agentic AI to monitoring, automation, or incident management.

Responsibilities

• Design end-to-end monitoring for VMs, Kubernetes, and bare-metal servers.
• Define layered monitoring covering hardware to applications.
• Set standards for metrics, logs, alerting, dashboards, SLIs/SLOs.
• Architect tool roles, data flows, retention, and HA for observability.
• Define alert policies and incident workflows to reduce noise.
• Map service topology and dependencies for infrastructure and apps.
• Ensure security and compliance for observability platforms.
• Build and maintain monitoring with Zabbix and dashboards with Splunk/Grafana.
• Automate configuration and onboarding of monitoring via IaC and APIs.
• Explore AI agent integration for triage, correlation, and remediation.

Skills

Observability design

SRE mindset

REST APIs

Tools

Zabbix

Splunk

Prometheus

Grafana

Kubernetes

VMware

Hyper-V

KVM

Job description

Overview

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~16,800 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

We are looking for a Senior Observability Engineer to design, build, and continuously improve monitoring and observability for our enterprise environment. Most of the work focuses on on-premises systems: physical servers, virtualized infrastructure, and on-prem Kubernetes clusters, along with the infrastructure layers underneath them. Some cloud use cases are also in scope. Your goal is to give system owners and business stakeholders an accurate, actionable view of the health and uptime of the systems they depend on. You will also help shape how we apply agentic AI to observability, moving from dashboards and alerts toward intelligent triage, correlation, and assisted remediation.

Responsibilities

Architecture and Design

• Design end-to-end monitoring and observability solutions for enterprise applications running on VMs, Kubernetes, and bare-metal servers, and extend them to cloud workloads where needed.


• Define a layered monitoring strategy that covers hardware, OS, virtualization, network, storage, platform services, and applications.


• Set standards for metrics, logs, alerting, dashboards, and service health models, including SLIs and SLOs where they apply.


• Make sound architectural decisions on tool roles, data flows, retention, scalability, and high availability across the observability stack.


• Define alert escalation policies, incident response workflows, and event correlation strategies to reduce operational noise and improve service reliability.


• Design service topology, dependency mapping, and business service monitoring across infrastructure and application layers.


• Secure observability platforms and integrations through access controls, authentication, encryption, and vulnerability remediation. Maintain compliance with enterprise security standards through platform hardening, audit readiness, and regular security reviews.

Implementation

• Build and maintain monitoring with Zabbix, covering templates, discovery, triggers, proxies, and integrations.


• Design and maintain log collection, parsing, enrichment, and routing pipelines into Splunk, including forwarders, sourcetypes, field extractions, indexes, and searches.


• Contribute to metrics and visualization with Prometheus and Grafana, particularly for Kubernetes workloads and unified dashboards.


• Automate the configuration and onboarding of monitoring using infrastructure-as-code and APIs.

Agentic AI for Observability

• Design and implement AI agents that support observability workflows. Examples include alert triage and deduplication, cross-source event correlation, root-cause hypotheses, incident summarization, and runbook-driven remediation with human-in-the-loop approval.


• Integrate LLM-based agents with monitoring and logging platforms through APIs and tool protocols such as MCP.


• Define guardrails, permission boundaries, and auditability for AI-driven actions on production systems.


• Measure the real impact of these agents on operations, for example on MTTD, MTTR, alert noise, and on-call load.

Collaboration

• Work closely with system owners to understand architecture, failure modes, and dependencies, and to translate them into meaningful monitoring.


• Partner with consumers and stakeholders of those systems to define what "healthy" and "available" mean to them, and to make sure observability gives them the visibility they need.


• Provide technical leadership and mentoring, and run knowledge sharing across operations, infrastructure, and development teams.

Continuous Improvement

• Regularly review alert quality, coverage gaps, and signal-to-noise ratio, and tune or retire monitoring accordingly.


• Use incidents and post-mortems as input to improve detection and response.


• Track the evolution of the observability toolset and the wider technology landscape.

Qualifications

Required

• 5+ years in infrastructure, operations, or observability engineering, with at least 3 years focused on monitoring and observability, primarily in on-premises enterprise environments.


• Hands-on, production-level experience with Zabbix and Splunk.


• Proven experience monitoring physical servers, virtualization platforms (e.g., VMware, Hyper-V, KVM), and Kubernetes clusters.


• Strong understanding of infrastructure layers: compute, OS (Linux and Windows), networking, storage, and the dependencies between them.


• Solid experience with log collection and processing at scale: parsing, normalization, enrichment, retention, and search optimization.


• Practical experience applying agentic AI (LLM agents, tool use, automation) to monitoring, operations, or incident management, along with a working understanding of how these systems behave and where their risks lie.


• Experience designing monitoring architecture, not only operating existing tools.


• Experience defining alert escalation policies, incident response workflows, and event correlation strategies to reduce operational noise and improve service reliability.


• Experience designing service topology, dependency mapping, and business service monitoring across infrastructure and application layers.


• Working knowledge of securing observability platforms, including access control, authentication, encryption, and hardening.


• Strong scripting skills (e.g., Python, Bash, PowerShell) and comfort working with REST APIs.


• Excellent communication skills and the ability to work with both technical owners and non-technical stakeholders.

Nice to Have

• Experience with Prometheus (exporters, alerting rules, Alert manager, long-term storage).


• Experience with Grafana (dashboard design, multi-source visualization, alerting).


• Experience monitoring cloud workloads (AWS, Azure, or GCP) and hybrid environments.


• Software development experience, such as building integrations, tools, exporters, or services.

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