Top AWS Jobs in Pune

Develop and maintain batch and real-time data pipelines using Java, Python, Spark, SQL, and Kafka. Build ETL/ELT solutions across data lakes and warehouses, perform data validation, optimize processing, and support cloud deployments, CI/CD, monitoring, and production troubleshooting. Collaborate with engineering and platform teams while developing reusable components and data pipelines supporting analytics, machine learning, and generative AI initiatives.

Leads complex, cross-functional technology programs across engineering, architecture, product, security, infrastructure, and operations teams. Owns program planning, dependencies, risks, delivery milestones, migrations, modernization, release governance, operational readiness, executive reporting, and incident war rooms. Drives alignment, resolves blockers, improves governance and delivery predictability, and mentors TPMs and project leads.

Leads architecture and design for scalable, highly available payment services. Responsibilities include creating high-level and low-level designs, developing critical components, preparing proofs of concept, conducting code reviews, mentoring engineers, documenting designs, managing source control operations, evaluating technologies, and improving engineering processes. The role requires expertise in Java, Spring, databases, NoSQL, messaging, microservices, cloud deployment, testing, Agile practices, security concepts, and enterprise application design.

Develop and maintain scalable cloud-based applications using Java and Spring Boot. Collaborate with product and engineering teams, implement microservices and APIs, ensure security and code quality, and support testing, deployment, monitoring, and incident remediation. Contribute to CI/CD automation, Agile ceremonies, technical documentation, proof-of-concepts, and AI-assisted software development practices. Work with relational and NoSQL databases, containers, DevOps tools, and emerging AI technologies.

Lead test automation, SRE, DevOps, and infrastructure automation initiatives for Mastercard’s cloud-native Priceless Platform. Build automated testing frameworks, CI/CD integrations, observability, monitoring, and deployment automation. Improve reliability, scalability, security, and release velocity through chaos engineering, performance testing, capacity planning, incident response, and disaster recovery practices. Mentor engineers, lead technical reviews, support production systems, and foster shared ownership and continuous improvement.

Collaborates with internal and client teams to analyze business problems, translate requirements into technical designs, and implement technology solutions. Develops technical features using appropriate methodologies, testing practices, and technology stacks. Supports project implementation planning, interprets business requirements, and contributes to small- and medium-scale client engagements involving databases, programming, cloud platforms, and analytics.

Supports technology projects through requirements gathering, technical discovery, functional specifications, API and data modeling, integration analysis, testing documentation, application troubleshooting, and stakeholder collaboration. The role translates business needs into implementation-ready designs, performs functional gap analysis, supports Agile delivery, manages risks, and coordinates with development teams, vendors, and business stakeholders across enterprise insurance systems.

Leads a Pune-based software engineering team building and operating shared data platform capabilities. Responsibilities include managing and developing engineers, shaping technical direction with product management, improving production data pipelines, migrating legacy workloads to cloud platforms, automating customer onboarding, enforcing data quality and security standards, managing incidents, coordinating vendors, and communicating progress to senior leaders. The role is 40–50% hands-on and requires recent Databricks and AWS experience.

Design, develop, test, deploy, and maintain scalable full-stack payment services using Java, Spring Boot, microservices, modern front-end frameworks, and cloud-native platforms. Build automation frameworks, validate APIs and integrations, improve security and reliability, troubleshoot complex issues, participate in architecture and Agile delivery, and mentor junior engineers.

Designs, builds, and operates production-grade agentic AI systems using Python, LLM orchestration, tool calling, retrieval, memory, multimodal models, and LLMOps. The role develops scalable backend services, observability, RAG and Graph-RAG systems, model evaluation, and responsible AI safeguards. It also mentors engineers, establishes GenAI engineering standards, and productionizes emerging AI capabilities across enterprise applications.

Build and operate production-grade agentic AI systems, including tool-calling layers, Python backend services, multi-agent orchestration, memory, retrieval, observability, LLMOps, and multimodal pipelines. Develop RAG and Graph-RAG systems, fine-tune and evaluate foundation models, implement responsible AI controls, and mentor engineers. The role requires strong backend engineering, API integration, cloud, distributed systems, and production LLM application experience.

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.

Designs, deploys, and drives adoption of New Relic observability solutions for strategic customers. Architects scalable monitoring for microservices, serverless, and distributed systems; integrates observability with cloud platforms, IaC, CI/CD, and platform engineering workflows; leads technical workshops; troubleshoots deployments; and creates documentation, training, and implementation best practices.

Develop secure, scalable full-stack applications using Java, Spring, REST APIs, frontend frameworks, cloud platforms, microservices, and databases. Collaborate with product owners and technical teams on architecture, Agile planning, coding, testing, deployment, and support. Work with Databricks, Spark, ETL pipelines, AI/ML services, containerization, CI/CD, and modern development tools while contributing to application design and user experience.

Designs, builds, and operates production-grade agentic AI systems and generative AI applications. Responsibilities include tool-calling infrastructure, Python backend services, agent orchestration, memory and retrieval systems, observability, LLMOps/MLOps pipelines, multimodal AI, model adaptation, responsible AI, and production evaluation. The role also mentors engineers and establishes engineering standards for enterprise generative AI development.

Lead architecture and technical strategy for an enterprise generative AI platform supporting agentic systems, tool calling, multi-agent orchestration, memory, retrieval, inference, LLMOps, observability, security, and responsible AI. Define reusable standards, evaluate models and platforms, guide architecture decisions, collaborate with engineering, product, security, and data teams, mentor technical leaders, and build prototypes for high-scale, reliable production systems.

Develop secure, scalable full-stack applications using Java, Spring, REST APIs, relational databases, and modern frontend frameworks. Responsibilities include designing software, building responsive interfaces, participating in architecture and Agile ceremonies, supporting testing, and collaborating with product and technical teams. The role also involves cloud deployment, microservices, CI/CD, containerization, Databricks and big data workflows, and integrating AI/ML services and development tools.

Develop scalable, highly available Java enterprise applications and microservices for Mastercard’s Account Level Management platform. Responsibilities include low-level design support, effort estimation, unit and integration testing, peer reviews, mentoring, task reporting, process compliance, and knowledge sharing. The role involves cloud deployment, database and messaging technologies, Agile development, security practices, and collaboration with engineering teams to deliver quality software on schedule.

Build, test, release, monitor, and support platform services, APIs, connectors, and automation for customer data exchange and pipeline orchestration. Deliver components independently, write tests and documentation, replace manual processes with code, investigate production issues, and contribute to design, estimation, code reviews, and root cause analysis. The role uses cloud technologies, data platforms, secure coding practices, and CI/CD.

Leads client-facing technology consulting engagements for manufacturing and industrial operations. Responsibilities include OT and industrial data strategy, solution architecture, SDLC delivery, Unified Namespace and data-layer design, client relationship management, account expansion, cross-functional team leadership, validation, change management, and ROI delivery. The role requires deep expertise in plant-floor systems, industrial connectivity, cloud, data engineering, and life-sciences or pharmaceutical manufacturing.

Leads the architecture, delivery, and evolution of scalable AI platforms and GenAI services. Manages and mentors engineering teams, oversees backend development using Python frameworks, guides LLM integrations and agentic workflows, establishes engineering standards, and owns technical delivery across multiple services. Partners with Product, AI/ML, DevOps, Data Engineering, and Consulting teams while ensuring production reliability, observability, security, and long-term platform sustainability.

Develop and maintain scalable full-stack enterprise applications using Java, Spring, React or Angular, microservices, and cloud-native AWS technologies. Responsibilities include requirements gathering, architecture and design, coding, testing, monitoring, performance engineering, compliance, and production support. The role also involves database development, CI/CD, DevOps, containerization, data engineering, and integration of AI/ML services. Candidates collaborate with business partners and technical teams while mentoring developers and ensuring secure, resilient, high-quality delivery.

Leads the design, automation, operation, and modernization of highly available Oracle and PostgreSQL database platforms across on-premises and AWS environments. Responsibilities include Infrastructure-as-Code, CI/CD, performance optimization, observability, disaster recovery, security, incident leadership, root cause analysis, and operational excellence. The role partners with engineering, SRE, security, and product teams while mentoring engineers and driving platform reliability and automation.

Provide frontline technical support for LogicMonitor users by managing incoming chat and ticket cases through resolution within SLAs. Troubleshoot SaaS IT infrastructure management issues across Linux, Windows, networks, containers, and cloud platforms. Educate customers, advocate for their needs, collaborate with product, development, and customer success teams on escalations, and contribute to product enhancements and bug resolution.

Serve as the senior technical advisor for strategic enterprise accounts, designing observability architectures across multi-cloud, hybrid, edge, and AI environments. Lead cloud migration observability, agentic AI monitoring, network pathing analysis, API integrations, automation, executive architecture reviews, workshops, and technical escalations. Partner with Sales, Customer Success, Product, Engineering, and AI teams to influence roadmaps and deliver scalable customer solutions.