Top DevOps Jobs in Pune

Lead the architecture and development of scalable full-stack Sales AI applications. Integrate generative AI models, retrieval systems, APIs, and agentic workflows into secure production solutions. Guide architecture across front-end, back-end, data, integrations, and cloud infrastructure while improving testing, delivery, observability, reliability, and maintainability. Lead technical decisions, investigate complex issues, mentor engineers, and collaborate with product, AI, data, security, and engineering teams.

Manages multiple data engineering teams responsible for enterprise-scale data transformation operations, data lakes, and analytics and AI/ML solutions on Google Cloud. Oversees staffing, coaching, budgets, demand management, delivery schedules, vendor resources, governance, and stakeholder relationships. Applies software engineering, DevOps, Scrum, Agile, product, and service management practices while coordinating cross-functional teams to deliver reliable data platform capabilities and automations.

Designs and governs enterprise AI, data, analytics, cloud, and platform architectures. The role develops AI reference architectures, data engineering standards, cloud infrastructure patterns, resilience controls, responsible AI frameworks, and technology roadmaps. It guides engineering teams, reviews strategic solutions, establishes governance, mentors technical staff, and partners with business, security, compliance, and senior leadership to enable scalable, secure, cost-effective AI and data platforms.

Develop and maintain scalable, reliable API applications using C#, .NET, C++, Azure, web services, and distributed systems. Responsibilities include object-oriented design, multithreading, design patterns, reverse engineering, SQL development, unit testing, acceptance test-driven development, DevOps collaboration, documentation, and working with distributed teams. The role requires strong ownership, communication, problem-solving, adaptability, and commitment to engineering quality.

Manages end-to-end technical projects, including scope, schedules, budgets, resources, risks, dependencies, technical documentation, quality assurance, and stakeholder communication. Coordinates engineering, product, IT, QA, vendors, and leadership to deliver software and technology initiatives. Applies Agile, Scrum, or Kanban methodologies, oversees deployments and integrations, tracks KPIs, ensures security and governance compliance, and supports post-implementation improvement.

Designs and manages AWS DevOps and CI/CD pipelines, build agents, release processes, automation scripts, and infrastructure using Terraform or ARM templates. Maintains Git repositories and branching strategies, integrates automated testing, applies cloud security practices, collaborates on vulnerability assessments, and implements monitoring, logging, and tracing solutions. Requires strong communication and problem-solving skills.

Develop and improve scalable, maintainable, and secure software solutions. Collaborate with product managers, designers, and engineers; participate in code reviews; implement unit testing; and support secure coding practices. The role also involves evolving infrastructure and deployment pipelines, managing operational excellence, and using Linux scripting, databases, DevOps tools, and C/C++ libraries. Kafka and Spring Boot experience is advantageous.

Support and develop large-scale OpenStack cloud infrastructure across multi-site deployments. Troubleshoot OpenStack services, PXE provisioning, networking, distributed systems, and third-party dependencies. Collaborate with SRE, platform, software, data center, and product teams to improve deployment quality, reliability, and time to market. Contribute Python and automation code while monitoring, investigating KPIs, resolving incidents, and supporting NVIDIA’s global engineering infrastructure.

Acts as a liaison among engineering, operations, and business stakeholders to execute product strategy. Manages and prioritizes the product backlog, creates user stories with Product Managers, and authors product lifecycle documentation including roadmaps, business requirements, and functional specifications. Participates in sprint planning, modernization and integration efforts, market research, competitive analysis, and iterative product development.

Build and maintain CI/CD pipelines, cloud infrastructure, and automated deployment processes. Implement Infrastructure as Code, manage Docker and Kubernetes environments, monitor system reliability, troubleshoot production issues, and support scalable software delivery. Collaborate with development and operations teams in an Agile environment while applying security and operational best practices.

Design and optimize scalable ETL/ELT pipelines and modern data platforms using Databricks, PySpark, Azure Data Factory, ADLS, Delta Lake, and Synapse Analytics. Develop data ingestion and transformation workflows, optimize Spark performance, implement CI/CD automation, and uphold data quality, security, and governance standards. Collaborate with architects, analysts, and business stakeholders on cloud-based data engineering solutions.

Designs, develops, configures, and supports enterprise-scale Fluent Commerce OMS solutions. Builds REST APIs, JSON integrations, webhooks, and asynchronous integrations with ERP, WMS, payment, CRM, loyalty, and eCommerce platforms. Responsibilities include testing, troubleshooting, production support, root cause analysis, code reviews, Agile ceremonies, and mentoring junior developers.

Lead engineering teams to deliver high-quality software by providing technical guidance, mentoring, overseeing delivery timelines, improving processes and tooling, enforcing standards, and collaborating with product and stakeholders. Drive DevOps/CICD, cloud, containerization, IaC, code quality and automation practices within the Mortgages digital domain.

Leads Workday integrations and packaged application implementations, including customization, module implementation, enterprise application integration, and development using Workday Studio, EIB, Core Connector, and Workday Extend. Builds and deploys custom Workday applications, coordinates cross-functional product launches, establishes platform best practices, and supports adoption. Applies expertise in HR, payroll, and compensation while exploring AI, machine learning, and intelligent automation capabilities.

Lead Workday integrations, packaged application implementations, custom Workday Extend app development, and cross-functional product launches. Configure Workday Studio, EIB, and Core Connector solutions; manage application lifecycles through production deployment; establish platform best practices; and support adoption through team development. Apply HR, payroll, and compensation domain knowledge while exploring AI, machine learning, and intelligent automation capabilities.

Build and deploy AI and machine learning solutions using distributed computing, cloud platforms, data pipelines, and production-grade software engineering practices. Responsibilities include technical requirements analysis, feature development, testing, code reviews, agile collaboration, architecture validation, and prototyping emerging technologies. The role partners with data scientists, architects, client-facing teams, and clients to deliver scalable AI solutions and manage machine learning lifecycles.

Develop and lead end-to-end features for scalable cloud-native SaaS applications using ReactJS, TypeScript, NodeJS, GraphQL, and modern cloud technologies. Translate customer and business needs into technical solutions, troubleshoot complex issues, mentor engineers, improve development processes, and guide adoption of emerging technologies, including AI-driven user experiences and workflow automation.

Build and manage cloud platforms, frameworks, and CI/CD infrastructure across production environments. Lead DevOps engineering practices, secure SDLC implementation, cloud architecture, infrastructure as code, Kubernetes and containerization initiatives. Mentor engineers, establish technical design standards, and promote DevOps culture. Design AI-assisted operational automation with appropriate security controls, governance, auditability, and human oversight for incident response, infrastructure management, deployments, and developer productivity.

Build and support scalable frontend and backend applications within Maersk’s People Technology team. Develop APIs, Generative AI solutions, copilots, and autonomous agents; configure and enhance Workday HR modules; and implement secure cloud-native services on Azure. The role includes DevOps, CI/CD, testing, incident management, change delivery, stakeholder advising, and Agile Scrum collaboration across Recruitment, Compensation, Benefits, and related HR systems.

Lead the architecture, modernization, integration, and governance of enterprise Adobe Experience Manager platforms. Design scalable Sites, Assets, headless, composable, and Edge Delivery Services solutions; guide migrations to AEM Cloud Service; and define integration, performance, security, and deployment strategies. Serve as the client CMS technology SME, lead technical teams and proofs of concept, mentor engineers, and advise on emerging Adobe capabilities. Collaborate with stakeholders to deliver reusable frameworks, modernization roadmaps, and AI-assisted development practices.

Leads enterprise AEM architecture, modernization, integrations, and digital experience platform strategy. Designs scalable Sites, Assets, headless, composable, and Edge Delivery Services solutions; guides technical teams and clients; establishes security, governance, performance, and deployment standards; and supports migrations to AEM as a Cloud Service. The role also mentors cross-functional teams, leads proofs of concept, evaluates emerging Adobe and AI-enabled capabilities, and translates complex technical recommendations into business value.

Senior DevOps Engineer responsible for improving developer productivity through CI/CD automation, build infrastructure, observability, and internal tooling. The role manages Jenkins, Harness, Kubernetes, Docker, artifact repositories, quality gates, and vulnerability scanning while tracking DORA metrics and optimizing build performance and reliability. The engineer partners with platform, engineering, and QA teams to streamline build, test, and deployment workflows.

Designs and operates scalable multi-cloud infrastructure across GCP and AWS. Responsibilities include Terraform provisioning, production Kubernetes management, observability, incident response, root cause analysis, CI/CD automation, cloud security, networking governance, and reliability improvements. The role collaborates closely with development, QA, and platform teams while participating in on-call rotations and optimizing cloud environments.

Build, operate, and continuously improve Azure cloud platforms and digital services using AKS, Kubernetes, Terraform, CI/CD, GitOps, Java, and Spring Boot. The role covers infrastructure automation, networking, security, observability, incident management, deployment operations, and developer experience improvements. It also supports reliable delivery of airport digital services and promotes standardized DevOps practices across agile teams.

Build and maintain reliable, scalable, and secure cloud infrastructure and deployment platforms. Develop automation, monitor system performance, manage incidents, implement security controls, and improve observability. Collaborate with product managers, architects, data scientists, and engineers to deploy digital solutions and machine learning models. The role also involves advising stakeholders, managing risk and controls, influencing technical decisions, and potentially leading or coaching team members.