Role Description We are seeking a highly skilled and self-driven Senior Software Engineer – Azure DevOps Engineer with deep expertise in Azure DevOps, Infrastructure as Code, and cloud automation. The ideal candidate will take full ownership of tasks from requirement gathering to development, handover, and troubleshooting, ensuring seamless delivery and minimal downtime across environments. Strong troubleshooting skills in Azure Cloud, excellent knowledge of Azure administration, and a solid understanding of networking concepts are essential. The candidate will leverage GitHub Copilot—including MCP-based context integrations—to accelerate specification-driven development, improve code quality, and automate test and deployment workflows. The candidate should have excellent communication skills, interpersonal skills, ownership and commitment. Experience in the healthcare domain is a plus. Job Responsibilities - Design, develop, and maintain advanced Azure DevOps YAML pipelines for CI/CD automation. - Write and maintain robust PowerShell scripts for automation, monitoring, and deployment tasks. - Develop and manage infrastructure as code (IaC) using Bicep for Azure resource provisioning. - Operationalize GitHub Copilot to ground code generation, improving speed and accuracy of feature delivery. - Take complete ownership of assigned tasks, including requirement analysis, implementation, documentation, and support. - Collaborate with cross-functional teams to understand deployment needs and deliver scalable DevOps solutions. - Proactively monitor and support development, testing, and production environments, ensuring high availability and minimal downtime. - Troubleshoot and resolve issues across the DevOps lifecycle, including build failures, deployment errors, and infrastructure problems. - Continuously improve DevOps practices, tools, and processes to enhance team productivity and system reliability. - Monitor and optimize infrastructure performance, cost, and security. - Mentor junior engineers and contribute to knowledge sharing within the team. Qualifications - 6–9 years of hands-on experience in Azure DevOps. - Proven expertise in Infrastructure as Code (IaC) using Bicep and ARM templates. - Strong experience in building and maintaining Azure DevOps (ADO) YAML pipelines for CI/CD. - Advanced scripting skills in PowerShell and YAML; familiarity with Unix Shell scripting is a plus. - In-depth knowledge of Azure Cloud services, including compute, storage, networking, and security. - Proven experience using GitHub Copilot in day-to-day development and demonstrable expertise configuring and using Copilot with MCP. - Strong troubleshooting and diagnostic skills for Azure deployments and infrastructure issues. - Solid understanding of Application Gateway, Azure networking, including Hub-Spoke architecture, NSGs, VNets, and routing. - Proficiency in Git and source control workflows. - Experience with .NET and RDBMS is a plus. Educational Requirements - UG: B. Tech / B.E. - Any Specialization, Computers, Electronics/Telecommunication - PG: MS/M.Sc. (Science) – Any Specialization, M.Tech – Any Specialization, MCA – Computers Benefits - Flexible working hours to create a work-life balance. - Opportunity to work on advanced tools and technologies. - Global exposure to not only collaborate with the team, but also to connect with the client portfolio and build professional relationships. - Highly encouraged for any innovative ideas & thoughts and we support in executing the same. - Periodical and on-spot rewards and recognitions on your performance. - Provides a better platform for enhancing skills via many different L&D programs. - Enabling and empowering atmosphere to work along.

• Own reliability for Volcano end-to-end: Define and drive SLOs, error budgets, and incident response practices for all Volcano services • Architect the platform's infrastructure: Design and build the multi-region Kubernetes infrastructure • Build the GitOps and CI/CD backbone: Establish deployment automation, canary pipelines, and preview environment provisioning • Scale managed data services: Design, operate, and harden multi-tenant PostgreSQL clusters • Drive observability from day one: Instrument every Volcano service with meaningful SLIs • Lead cross-functional reliability work: Collaborate with the OCTO team, product engineering, and security to bake reliability into Volcano's architecture • Set SRE culture and standards: Mentor engineers on reliability principles; lead postmortems • Evaluate and adopt emerging technologies: Given Volcano's greenfield nature, evaluate edge runtimes, serverless compute, vector databases, and AI-native infrastructure components.

• As a Senior DevOps Engineer at Incode, you’ll be a senior individual contributor on the platform team responsible for operating, scaling, and securing the production systems behind Incode’s identity infrastructure. • You’ll own outcomes - not tickets - across our Kubernetes and AWS environments, partnering closely with software engineers, security, and leadership to make our platform faster, safer, and quieter. • You won’t just keep the lights on; you’ll improve reliability, reduce operational friction through automation, and lead durable fixes when things break.

• Serve as the senior technical counterpart to AWS field leadership, building trust and credibility across regions and teams. • Influence joint account strategy and technical direction for high-priority opportunities. • Shape how OpenAI engages with AWS by defining engagement models, prioritization frameworks, and best practices. • Proactively identify and drive net-new opportunities and high-impact use cases across the AWS ecosystem. • Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements. • Guide customers from early ideation through architecture design, prototyping, and production deployment. • Act as a technical decision-maker and escalation point, de-risking complex implementations. • Design and communicate end-to-end AI architectures leveraging OpenAI and AWS services. • Build and guide development of prototypes, POCs, and reference implementations to accelerate adoption. • Establish best practices for scalable, secure, and production-ready GenAI systems. • Enable AWS and partners through scalable technical motions (workshops, playbooks, reference architectures, demos). • Develop reusable solution patterns and assets that can be deployed independently by AWS teams and SIs.