Top AWS Jobs in Pune

Designs, builds, tests, and maintains scalable full-stack analytics applications, responsive user interfaces, data models, APIs, and data pipelines. Partners with product managers and designers to deliver customer-focused features, improves development processes, reviews code, mentors junior engineers, and collaborates across global teams. The role requires strong Java and modern web development expertise, cloud-native experience, distributed systems knowledge, automated testing skills, and proficiency in agile software engineering.

Manages multiple software engineering teams developing and supporting payment fraud and transaction resilience applications. Responsibilities include hiring, coaching, performance management, budgeting, technical strategy, architecture, code quality, security, vulnerability management, technical debt prioritization, capacity planning, incident reduction, CI/CD automation, release testing, and performance testing. Requires strong Java development experience and expertise with Spring Boot, secure coding, operating systems, application troubleshooting, design patterns, and engineering productivity practices.

Build and productionize AI-powered applications, backend services, RAG solutions, MCP integrations, and agentic workflows. Translate requirements into secure, scalable software; establish AI evaluation and validation standards; implement testing, CI/CD, observability, resilience, privacy, compliance, and Responsible AI controls. Collaborate with cross-functional teams to deliver reliable enterprise solutions in an Agile environment.

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.

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.

Leads the architecture and delivery of secure, scalable enterprise infrastructure across on-premises, hybrid-cloud, and cloud environments. Partners with engineering, security, network, and product teams to drive platform modernization, automation, Infrastructure-as-Code, resiliency, performance, and operational excellence. Develops architecture standards, roadmaps, and documentation while ensuring availability, compliance, disaster recovery, and security requirements for mission-critical platforms.

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.

Designs, develops, supports, and optimizes scalable data pipelines and distributed processing workloads. Writes production-grade Python, PySpark, and SQL; tunes Spark and SQL performance; troubleshoots Linux and AWS infrastructure; improves monitoring, reliability, security, and cost efficiency; performs root cause analysis; and collaborates with engineering, product, architecture, and operations teams. The role also supports AI-enabled data workflows using LLMs, Amazon Bedrock, Agentic AI, and MCP.

Architect and deliver high-performance Angular-based UI experiences for SailPoint’s cloud SaaS product. Build responsive TypeScript components, define REST API contracts with microservices teams, resolve customer UI issues, improve frontend architecture and automated test coverage, and prevent critical regressions. The role also includes mentoring engineers, collaborating with UX and Product Management, estimating quarterly epics, and leading frontend architecture planning in an Agile environment.

Leads the design, modernization, development, and deployment of Java microservices applications. Provides technical direction to backend and SDET teams, designs REST APIs and distributed integrations, manages Kubernetes deployments and CI/CD pipelines, and coordinates regional releases. Responsibilities include code and architecture reviews, performance optimization, observability, secure coding, automated testing, production troubleshooting, incident management, and stakeholder coordination.

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.

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.

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.

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.

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.

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.