SRE Engineer (3-6 years) - Hybrid - Bengaluru

World Wide Technology; Bengaluru; Hybrid; INR 1,800,000 - 3,000,000; Full time

Job summary

World Wide Technology in Bengaluru offers a Hybrid SRE Engineer role focused on AI-powered production intelligence. You will help teams measure the health of global SaaS services, integrate AI agents and scalable workflow tooling, and drive reliability across Kubernetes clusters.

You will work with a global Cisco-backed collaboration stack, applying SRE, CI/CD and DevOps practices to deliver dependable, scalable systems and proactive incident response.

Qualifications

• Proficient in software engineering with hands-on coding experience.
• Experience with observability, incident response and AI-assisted engineering.
• Proficiency in Python, Java or Go and building automation/services in production.
• Experience supporting SaaS on Docker and Kubernetes.

Responsibilities

• Build AI-assisted tools and workflows for production health visibility and decision support.
• Convert logs, metrics, traces, alerts and runbooks into actionable insights for teams.
• Accelerate RCA and incident investigations across distributed SaaS services and clusters.
• Develop proactive detection and automated remediation workflows for reliability.
• Engineer and operate microservices on Kubernetes with CI/CD and automation.
• Tune applications for reliability, performance and scalability.
• Evaluate AI output for safety, security and usability.
• Solve complex production problems across the stack.

Skills

Strong software engineering

Observability & incident response

Python/Java/Go

Docker & Kubernetes

Tools

Git

Jenkins

AWS

GCP

Azure

Docker

Kubernetes

CI/CD tooling

AI/LLM tooling

Job description

Worldwide Technology (WWT), a 36-year-old global technology solutions provider specializing in systems integration, Infra-Cloud security, application development, AI Services, and supply chain solutions. With a workforce of 10,000+ employees and strategic partnerships with leading OEMs such as Cisco, Dell EMC, Microsoft, and NVIDIA, WWT delivers cutting-edge infrastructure, cloud, security, and custom application services to clients across 35 countries. Our Advanced Technology Centers (ATCs)lab setup environments spanning over one million square feet of world-class integration and distribution space enable us to deliver unmatched value and innovation at scale. Recognized as one of the Best Places to Work by Glassdoor and Fortune for 14 consecutive years, WWT is also ranked #6 on Indias Great Place to Work list for 2025.

Worldwide Technology Holding Co, LLC. (WWT) currently has an exciting opportunity available for the role of Site Reliability Engineer Hybrid Opportunity at Bengaluru.

SRE Engineer

What You’ll Do

As a member of a dynamic and international team, you will help build AI-powered production intelligence capabilities that enable SRE, Engineering and executive stakeholders to understand the health of our global SaaS services quickly and confidently.

You will combine Cloud Native and SRE practices with AI technologies - including AI Agents, reusable Skills, MCP and LLM tooling - to accelerate incident root cause analysis, surface actionable operational insights and proactively detect potential production issues across Kubernetes clusters.

The role will involve:

• Build AIassisted tools and agentic workflows for production health visibility and decision support
• Turn logs, metrics, traces, alerts, changes and runbooks into actionable insights for SRE, Engineering and executive audiences
• Accelerate incident investigation and RCA across distributed SaaS services and Kubernetes clusters
• Develop proactive detection, anomaly analysis and safe remediation workflows
• Engineer and operate microservices on Kubernetes using SRE, CI/CD and automation practices
• Tune applications and platforms for reliability, performance and scale
• Evaluate AI output quality, security, safety and usability
• Complex problem solving

You will be expected to work towards deadlines whilst effectively managing priorities and communicating progress. You will work across teams to turn production needs into dependable software and AI-assisted operational capabilities.

You have the convenience to interact with Cisco Webex teams globally using our own collaboration technologies, and on occasion through travel.

Who You’ll Work With

The Collaboration Technology Group is redefining the future of collaboration. We are creating a world where people come together effortlessly on their own terms and with no limitations on device, location, time or distance. Our group builds cutting-edge collaboration technologies, deployed daily to numerous datacentres around the world.

We are a fun, passionate and upbeat team within Cisco with a mission to build, run and improve the underpinning platform services which make our offering the best-in-class collaboration services possible, at an unprecedented scale.

Who You Are

You are a hands-on engineer who enjoys solving ambiguous production problems and turning operational data into clear decisions. You work effectively across development and operations, communicate with technical and executive audiences, and apply AI with sound judgement, careful validation and respect for security and privacy.

Required Skills

• Strong software engineering fundamentals and the ability to learn quickly
• Practical observability, incident response and AI/LLM-assisted engineering experience, with careful validation of generated output
• Proficiency in Python, Java or Go and experience building production-quality automation or services
• Experience supporting SaaS services running on Docker and Kubernetes

Desired Technical Skills

• Source control and CI/CD tooling (Git, Jenkins or equivalent)
• Public cloud platforms (AWS, GCP, Azure or equivalent)
• Distributed systems, microservice architecture and service dependencies
• Logs, metrics, traces, alerting and observability stacks
• Incident investigation, root cause analysis and operational runbooks
• AI Agents, reusable Skills, MCP or comparable tool-integration patterns
• Prompt design, retrieval workflows and evaluation of LLM output
• Safe AI automation, guardrails and responsible AI practices
• Proactive detection, anomaly analysis and automated remediation
• Performance, capacity, reliability and scalability engineering
• Databases, streaming platforms and messaging queues
• SRE principles, error budgets and continuous improvemen