Top AWS Jobs in Pune

Lead the technical direction, reliability, security, and scalability of platform infrastructure, deployment pipelines, and operational automation, especially within a FedRAMP environment. Design infrastructure-as-code, improve observability and incident response, build microservice automation, guide platform migrations, partner with security and compliance teams, and mentor engineers.

Lead architecture, design, development, and delivery of Mastercard’s cloud-native experimentation and analytics platform. Build scalable services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and modern engineering practices. Drive modernization, architecture reviews, technical strategy, cross-team execution, system reliability, security, observability, and continuous delivery while mentoring engineers and collaborating across globally distributed teams.

Leads and develops a high-performing software engineering team building full-stack business experimentation and optimization applications. Responsibilities include supervising and mentoring engineers, designing scalable service-oriented architectures, leading projects from inception through release, developing software, reviewing code, planning features, improving engineering processes, and collaborating across teams. The role requires expertise in full-stack, data, cloud, microservices, databases, and advanced software development practices.

Operate and improve multi‑cloud (AWS/Azure/hybrid) platforms with SRE practices: lead incident triage and RCA, manage Kubernetes and CI/CD pipelines, implement IaC and automation, enhance observability/AIOps, and drive DevSecOps and operational excellence across global 24x7 operations.

Performs manual penetration testing of web, mobile, API, and microservices applications; conducts secure code reviews and design assessments; identifies and validates vulnerabilities; documents findings; supports remediation and incident response; guides junior testers; and promotes secure coding and application security awareness.

Design and develop a scalable automated locates platform for securities finance using Java, Spring, microservices, distributed systems, containers, AWS, SQL, caching, and messaging technologies. Build high-performance enterprise applications, optimize transactional data models and queries, integrate real-time processing systems, and collaborate with development, business analysis, QA, and operations teams.

Support data governance policy implementation, data discovery, classification, cataloging, quality monitoring, metadata and lineage documentation, risk assessments, audits, tool administration, and remediation. Partner with data owners, stewards, and IT teams to promote secure, compliant, and trusted data. Provide training, user support, workflow assistance, and governance dashboards for leadership.

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.

Designs and reviews security architecture, performs threat modeling and cloud assessments, responds to incidents, manages security tools, and advises engineering teams on secure development. Conducts code and vulnerability reviews using OWASP and MITRE ATLAS, evaluates AI and LLM security risks, and supports security monitoring, risk assessment, data protection, and compliance across applications, infrastructure, and endpoints.

Leads the architecture, design, and delivery of secure, scalable, resilient infrastructure across data center, hybrid cloud, and distributed environments. Partners with engineering, security, networking, cloud, product, and program teams to deliver modernization initiatives, automation, Infrastructure-as-Code, platform standardization, and operational excellence. Develops architecture standards and roadmaps while ensuring availability, compliance, disaster recovery, performance, and security for mission-critical platforms.

Build and maintain large-scale backend data systems, batch and streaming pipelines, datamarts, and cloud data workloads. Develop AI-powered agents for anomaly detection and workflow automation, using Scala, Python, Java, Spark, Cloudera, Databricks, and AWS. Support platform reliability, data integrity, downstream analytics, documentation, Agile collaboration, and team mentoring.

Build data engineering solutions that ingest, aggregate, unify, and analyze high-volume data from diverse sources. Develop data pipelines and models using Cloudera, Databricks, AWS, Hadoop, Python, and SQL. Partner with product, data science, platform, technology, client, and sales teams to deliver actionable insights, prototypes, business intelligence, and innovative cyber, fraud, security, and digital identity products.

Build and maintain scalable full-stack, data-intensive applications for Mastercard’s experimentation platform. Develop frontend, backend, APIs, and data-processing layers using Java, Spring Boot, TypeScript, React, Databricks, and Spark. Contribute to architecture, system design, testing, code reviews, performance optimization, and operational excellence. Collaborate with Product, Data Engineering, QA, and global development teams to deliver analytics-driven solutions, mentor colleagues, and improve engineering quality and scalability.

Designs, automates, and optimizes enterprise Windows platforms using SCCM, Ansible, PowerShell, and Infrastructure as Code. Responsibilities include OS deployment, patching, software distribution, compliance enforcement, server build pipelines, CI/CD integration, self-service delivery, troubleshooting, capacity planning, and platform modernization. The role leads Wintel engineering workstreams, establishes automation standards, collaborates with infrastructure and security teams, and supports scalable, secure, and highly available services.

Lead design and build cloud-native batch and real-time data platforms. Develop scalable ETL/ELT and streaming pipelines (Spark, Kafka, Flink), ensure data quality, governance, observability, security, cost optimization, and drive platform engineering excellence and team mentorship.

Modernize security operations by building SOAR playbooks, AI-augmented investigation workflows, prompt libraries, Jupyter notebooks, response tooling, and integrations across SIEM, EDR, identity, ticketing, threat intelligence, and AI platforms. Partner with SOC and DFIR teams to automate high-effort processes, support major incidents, optimize response outcomes, maintain reusable tooling, and contribute to product roadmaps and technical documentation.

Develop and maintain secure, high-quality software components for Mastercard’s unified UI platform. Responsibilities include coding, testing, deployment, troubleshooting, refactoring, automation, API integration, release pipeline orchestration, and architecture understanding. The engineer will contribute to Agile processes, conduct demos, improve operational metrics, promote engineering standards, review code, mentor team members, and collaborate with product owners to deliver reliable, accessible customer experiences.

Build and operate production software and AI systems across cloud infrastructure. Responsibilities include developing APIs and services, operating RAG and inference platforms, implementing CI/CD and observability, managing AWS or GCP environments with Kubernetes and Terraform, optimizing model serving and GPU usage, controlling cloud and AI costs, and partnering with stakeholders on reliability, security, governance, and technical tradeoffs.

Architect generative AI workflows for cloud configuration and remediation using RAG, vector databases, and LLM APIs. Automate Terraform modules, Rego policies, and Regula test cases; develop AI-enabled drift detection, discovery, gap analysis, and remediation capabilities. Lead cloud security tooling AI initiatives, design extensible service architectures, establish technical strategy, and mentor engineers across a distributed global team.

Build backend-focused services using Java and Spring Boot, while maintaining an Angular frontend. Design RESTful APIs, transition database-centric systems toward domain-driven architecture, and work with PostgreSQL, Oracle, JPA/Hibernate, and complex SQL on high-transaction platforms. Collaborate within cross-functional squads to deliver scalable, high-quality features.

Build and maintain large-scale automated testing frameworks, libraries, infrastructure, and test suites for enterprise SaaS applications, APIs, services, and distributed systems. Integrate automation into CI/CD pipelines, troubleshoot application and production issues, validate AI-generated code and tests, improve coverage and reliability, and collaborate with engineering, DevOps, product, and QA teams. The role requires independently delivering extensive automation coverage and supporting issue reproduction outside standard hours when needed.

Designs and maintains large-scale automated testing frameworks, libraries, infrastructure, and suites for enterprise SaaS applications, APIs, services, and distributed systems. Integrates testing into CI/CD pipelines, troubleshoots application and production issues, validates AI-generated code, improves test coverage and reliability, and collaborates with engineering, DevOps, product, and QA teams. The role requires extensive hands-on programming, cloud experience, independent automation ownership, and occasional after-hours incident support.

Designs and maintains large-scale automated testing frameworks, libraries, infrastructure, and test suites for enterprise SaaS applications, APIs, services, and distributed systems. Develops production-quality automation, integrates tests into CI/CD pipelines, troubleshoots application and production issues, and expands test coverage using AI-assisted development tools. Collaborates with engineering, DevOps, product, and QA teams to improve reliability, observability, maintainability, and automation efficiency.

Lead architecture and design of cloud-native Java/Spring Boot microservices and full‑stack applications. Define HLDs/LLDs, cloud (Azure/AWS) architectures, containers/Kubernetes, event-driven patterns, and non-functional requirements. Guide legacy modernization, incorporate AI/GenAI where applicable, collaborate with product and governance, and mentor senior engineers to drive best practices.

Designs, implements, administers, and optimizes enterprise VMware and Nutanix virtualization environments. Leads datacenter migrations, infrastructure upgrades, platform consolidations, and modernization initiatives. Provides advanced troubleshooting, capacity planning, performance optimization, monitoring, root cause analysis, and operational support. Develops automation using PowerShell, PowerCLI, and Python, coordinates with stakeholders and vendors, creates technical documentation, and mentors junior engineers. The role operates within 24/7 rotational shifts.