Jobs›Staff Devops

Senior Staff DevOps Engineer

SailPoint · Work from home
Work from home
PayPay not listed
WhereWork from home
TypeFull timeSenior
Posted22 OctYesterday, via Himalayas
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Good spoken and written English expected
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Skills they list12 named
DevOps EngineerCloud InfrastructurePlatform EngineeringKubernetes EngineeringSenior Staff EngineerSenior Staff DevOps EngineerSr Staff DevOps EngineerStaff DevOps EngineerStaff Software Engineer DevOpsSenior DevOps Platform EngineerSenior DevOpsSenior DevOps Developer
About this job

About SailPoint

SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving customers unmatched visibility into their digital workforce and ensuring workers have the right access — no more, no less.

Built on a foundation of AI and machine learning, our Identity Security Cloud (Atlas) platform delivers the right level of access to the right identities and resources at the right time — matching the scale, velocity, and changing needs of today’s cloud-oriented enterprise. SailPoint is all-in on the AI revolution, and our engineers have access to the latest frontier models and agentic frameworks.

About the Role

As a Senior Staff DevOps Engineer on the Infrastructure Platform team, you will be a technical leader responsible for designing, building, and operating SailPoint’s global Identity Security Cloud infrastructure on AWS, Azure, and GCP. You will partner with engineering teams across India, the US, EMEA, and APAC to deliver a resilient, secure platform. You will be a key contributor to our AI-assisted and agentic automation and tooling.

You will serve as a Kubernetes platform leader for the team — guiding engineers on EKS and AKS operations, service mesh, and cloud-native deployment patterns across our production environments. You will also play a key role in supporting SailPoint’s PCI compliance initiative, helping ensure our platform infrastructure meets PCI DSS requirements.

This is a fully remote position for candidates based in India. The role carries significant technical influence across the organization — setting architecture direction, mentoring engineers, and driving operational excellence without requiring people management.

The ideal candidate is a self-starter who thrives in complex, fast-paced SaaS environments, enjoys solving hard infrastructure problems, brings expert-level Kubernetes, AWS platform, and modern AI knowledge, values quality and reliability, and is excited to thrive on an AI enabled team.

About the Team

The Infrastructure Platform Team designs and operates the foundational cloud infrastructure that powers SailPoint’s Identity Security Cloud. Our platform runs on a mature, cloud-native, event-driven microservices architecture on AWS, with Kubernetes, GitOps, and Infrastructure-as-Code at the core. We also support smaller environments in Azure and GCP.

Engineers in India work closely with global peers in the US, the UK, Israel, the UAE, and Mexico. The team owns all SailPoint’s cloud infrastructure, compute capabilities, and operational practices for a 24×7 SaaS environment serving large enterprises worldwide. We focus on GitOps and Infrastructure as Code, agentic automation, and managing web platforms that serves millions of concurrent requests.

Key Responsibilities

Multi-Account AWS Operations

Design, build, and maintain a resilient, secure, and cost-efficient multi-account AWS SaaS platform that meets established SLAs and uptime targets.

Design and evolve multi-account AWS architectures, guardrails, and IaC patterns.

Kubernetes Platform Leadership

Serve as a technical lead on Kubernetes for the Infrastructure Platform team — our platform is heavily Kubernetes-based, and this role requires deep, hands-on expertise.

Design, operate, and optimize production Kubernetes clusters at scale on AWS (EKS) and Azure (AKS), including cluster architecture, upgrades, node management, networking, storage, and multi-tenant isolation patterns.

Design, implement, and operate a service mesh (e.g., Istio, Linkerd, or AWS App Mesh) for microservices communication — including mTLS, traffic management, observability, resilience patterns, and progressive delivery across environments.

Define and drive Kubernetes and service mesh standards and best practices across teams — workload design, resource management, security hardening (RBAC, Pod Security Standards, network policies), Helm/chart conventions, and deployment patterns.

Guide and mentor engineers on Kubernetes and service mesh troubleshooting, performance tuning, capacity planning, and production incident resolution for containerized microservices.

Platform Architecture

Design and scale infrastructure to meet rapidly increasing customer demand, data sovereignty requirements, and regional expansion.

Define standards for AWS and Azure networking, IAM, secrets management, AWS Organizations governance, and cross-account connectivity.

Automate deployment, monitoring, incident response, and capacity management using GitOps and CI/CD best practices.

Develop and improve operational practices, runbooks, and platform engineering standards.

Collaborate with development teams to bring new features and services into production safely and efficiently.

Proactively meet information security and compliance standards (e.g.,PCI DSS), including supporting SailPoint’s PCI compliance initiative through secure platform design, controls implementation, and audit readiness.

Participate in and help improve the on-call rotation; drive post-incident reviews and systemic fixes.

AI & Agentic Workflow Innovation

Champion AI-assisted and agentic workflows across DevOps, SRE, and platform engineering — integrating LLM-based tooling, AI code assistants, and autonomous agents into day-to-day operations.

Design and operationalize agentic automation on AWS using services such as Amazon Bedrock, including model selection, prompt/orchestration patterns, and integration with operational tooling for tasks such as infrastructure code generation/validation, incident triage, root-cause analysis, deployment troubleshooting, compliance checks, and repetitive operational runbooks.

Establish guardrails, observability, cost controls, and human-in-the-loop practices for safe adoption of Bedrock-powered and AI-driven automation in production environments.

Partner with engineering leadership to define a roadmap for AI-native platform operations on AWS and measure productivity,

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