Senior DevOps Engineer

Granicus India

1d•Remote

About The Position

The Senior DevOps Engineer is an advanced engineering position responsible for designing, implementing, and supporting automation, deployment, monitoring, and operational reliability across cloud and hosted application environments, with expertise in applying AI to optimize platform operations. This role partners closely with software engineering, site reliability, security, infrastructure, and architecture teams to improve continuous integration and continuous delivery processes, infrastructure automation, platform operations, and service resilience across increasingly complex environments and delivery pipelines. The successful candidate will demonstrate deep hands-on experience with DevOps practices, cloud infrastructure, systems administration, automation, and troubleshooting, along with the ability to independently lead complex technical efforts from planning through implementation. This position is intended for senior engineers with demonstrated AI/ML experience who are expected to apply advanced technical judgment and drive significant improvements in platform reliability and efficiency by applying AI across CI/CD, observability, incident response, and infrastructure designing and operation—optimizing builds and pipelines; detecting and diagnosing failures faster; using predictive insights to spot anomalies and bottlenecks; and recommending cost and resource-utilization improvements, while also providing technical leadership, mentoring, and day-to-day guidance to other engineers. The role includes leadership of complex projects and technical workstreams, coordination across teams, and influence over engineering practices and delivery outcomes.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
Significant progressive professional experience in DevOps(8+ Years), platform engineering, systems engineering, cloud infrastructure, or a related engineering discipline.
Demonstrated advanced working knowledge of DevOps concepts, including CI/CD, automation, infrastructure as code, cloud operations, release management, system reliability, and operational resilience.
Strong hands-on experience with Linux and/or Windows administration, scripting, source control, cloud platforms, and troubleshooting in production or pre-production environments.
Practical experience with containers, infrastructure as code, monitoring, logging, operational support processes, and modern platform engineering practices.
Demonstrated ability to independently lead complex assignments and technical initiatives, manage competing priorities, and deliver reliable results in a fast-paced engineering environment.
Demonstrated experience leading complex projects or technical workstreams, including organizing tasks, coordinating stakeholders, managing dependencies, identifying risks, and driving work to completion.
Demonstrated ability to provide technical leadership, mentor engineers, and influence engineering practices, design approaches, and operational standards without formal people management responsibility.
Effective written and verbal communication skills and the ability to collaborate across technical teams while clearly communicating technical issues, risks, recommendations, project status, and implementation strategy.
Demonstrated accountability, sound judgment, attention to detail, and commitment to operational excellence, continuous improvement, and technical quality.
Ability to use approved AI-enabled tools responsibly to improve productivity, support troubleshooting, enhance documentation, and assist engineering workflows.

Nice To Haves

AI/ML experience

Responsibilities

Own and support software delivery activities, including build, deployment, release, and environment management processes across multiple complex applications and infrastructure environments.
Design, maintain, and optimize CI/CD pipelines used to build, test, secure, and deploy applications with greater efficiency, consistency, resiliency, and scalability.
Architect, provision, configure, and maintain infrastructure in cloud and hosted environments using automation and infrastructure as code practices.
Lead complex technical projects or cross-functional workstreams, including planning, dependency coordination, risk identification, execution oversight, and successful delivery of outcomes.
Provide technical leadership across DevOps and platform engineering initiatives by setting direction for implementation approaches, reviewing designs, promoting best practices, and influencing technical decisions.
Mentor and guide engineers through technical coaching, knowledge sharing, solution reviews, and hands-on support to improve team capability and delivery quality.
Troubleshoot and resolve complex application, deployment, infrastructure, and environment issues with minimal supervision, including active participation in incident response, root cause analysis, and follow-through on corrective actions.
Monitor system health, review logs and telemetry, and implement improvements in reliability, performance, scalability, recoverability, and operational efficiency.
Drive standardization of engineering practices, reusable automation, deployment patterns, architecture guardrails, and operational runbooks that improve consistency across environments.
Collaborate across engineering, support, operations, security, and architecture teams to resolve issues, support releases, manage dependencies, and improve platform and delivery processes.
Apply established security, compliance, and operational standards in all engineering activities and identify opportunities to strengthen controls, reduce risk, improve resilience, and increase audit readiness.
Participate in operational support and on-call activities, and take ownership of critical issues through resolution, communication, and follow-through.
Lead the design and architecture of AI-driven DevOps platforms across CI/CD, observability, and operations.
Drive organization-wide adoption of AI, MCP frameworks, and AIOps practices.
Define standards for AI usage, governance, security, and compliance across engineering workflows.
Architect end-to-end AI-enabled automation ecosystems (agents, workflows, deployment intelligence).
Use AI to influence strategic decisions (capacity planning, cost optimization, and reliability engineering).
Mentor engineers and lead initiatives to scale AI capabilities, frameworks, and best practices.
Have experience using Python (or similar) to build operational tools with guardrails.