Sr Staff Software Engineer

ServiceNow · Hyderabad, Telangana, India

  • Senior
  • Full-time
  • Posted 2026-09-24
  • Confirmed live on 25 September 2026

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Job description

Job Description
Position Overview
ServiceNow is seeking a highly motivated and experienced Senior Staff Software Engineer for platform engineering across DevOps, Deployment, and Performance Engineering functions within the PAXE DevOps & Performance Engineering organization. This role sits at the intersection of developer productivity, AI-native tooling, and operational excellence, owning the systems and practices that enable teams to ship with speed and confidence.

As a technical anchor on the team, you will drive the strategy and execution for CI/CD pipeline enablement, the cross team AI development platform, and shift-left performance engineering. You will work closely with partner organizations including framework, UX and other engineering teams to build the infrastructure and tooling that powers how AI is built, tested, and delivered at ServiceNow. Success in this role requires strong cross-functional collaboration aligning on developer experience, end-to-end delivery, and platform teams on observability and release quality. This role offers high executive visibility and the opportunity to shape foundational engineering practices across the organization.

Key Responsibilities
DevOps & Release Engineering

• Lead design and execution of CI/CD pipeline enablement, working with devProd to improve developer throughput, greenlight processes, and merge guidance.

• Own the Application Rating Tool and observability infrastructure, partnering with platform teams to surface actionable engineering metrics via a centralized dashboard.

• Drive the all Pods technically, establishing scalable testing patterns across frameworks and applications built on Karuna.

• Build and maintain the IT initial triage agent, applying AI to automate first-line engineering support.

Cross team delivery Platform

• Own the cross team platform roadmap.

• Architect and implement batch API strategies to avoid API rate-limit thresholds and improve platform reliability.

• Build and iterate on the Pod Coach / Scrum Master agent, applying agentic AI to improve team delivery workflows.

• Drive MCP integration and lead weekly communications, demos, and governance meetings to align stakeholders and scale adoption.

• Maintain documentation and program-level visibility.

Performance Engineering

• Lead a shift-left performance strategy, embedding client, API, and page-load performance tooling earlier in the development lifecycle.

• Define and drive performance monitoring requirements for Lit based framework and application-level workloads.

• Own the Performance Tooling efforts, reporting infrastructure, and test data strategy.

• Coordinate with the broader Performance Engineering team on MCP integration and result triage workflows.

Technical Leadership

• Act as a technical leader and mentor, setting engineering standards, driving code quality, and fostering a culture of continuous improvement.

• Champion the use of AI to accelerate DevOps and platform engineering including AI-assisted PR reviews, skill/agent development, deployment recommendations, test generation, and predictive monitoring.

• Partner with Engineering Managers and cross-functional teams to align on roadmap priorities, delivery milestones, and operational health.

Qualifications
• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.

• 12+ years of software engineering experience in a high-traffic, cloud-based environment, with at least 3 years in a senior or staff-level individual contributor role.

• Strong proficiency in Java, javascript and/or Python, with solid understanding of distributed systems, concurrency, and scalable service design.

• Deep hands-on experience with CI/CD platforms (e.g., Jenkins, GitHub Actions) and modern DevOps tooling at scale including pipeline design, build optimization, and release automation.

• Expert-level knowledge of Kubernetes and container orchestration

• Strong observability and monitoring background — hands-on with Grafana, Prometheus, OpenTelemetry, or equivalent stacks; able to design and instrument dashboards, alerts, and SLO/SLI frameworks across distributed services.

• Experience operating and debugging services on Kubernetes clusters — log aggregation, tracing, resource profiling, and incident response in containerized environments.

• Demonstrated experience building and operating developer productivity or internal platform tooling.

• Understanding of performance engineering concepts including load testing, API latency profiling, page-load optimization, and shift-left testing strategies.

• Track record of applying AI/ML or agentic AI to engineering workflows; experience with MCP, A2A, or AI-native development platforms is a strong plus.

• Excellent cross-functional collaborati

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