Top AWS Jobs in Pune

Manages software engineering teams and owns end-to-end delivery of analytics and business intelligence solutions. Responsibilities include people management, technical strategy, architecture and system design, code and deliverable reviews, quality and security oversight, technical debt management, innovation, stakeholder coordination, and Agile delivery. The role requires expertise in React.js, .NET, AWS, databases, Hadoop, Spark, Databricks, big-data analytics, CI/CD, DevOps, and automation.

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.

Leads Mastercard’s Site Reliability Engineering strategy for critical payment platforms. Oversees reliability, resiliency, scalability, performance, observability, incident management, automation, production readiness, and operational governance. Provides strategic, technical, and people leadership while building globally distributed teams and partnering with engineering, infrastructure, cybersecurity, and product stakeholders. Drives modern SRE and DevOps adoption, regulatory risk management, AI-assisted operations, and continuous improvement across payment networks.

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.

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.

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.

Designs, develops, tests, and maintains Java-based backend services using Spring Boot, distributed systems, messaging, and cloud-native technologies. The role includes architecture contributions, performance optimization, secure coding, code reviews, mentoring, troubleshooting, root-cause analysis, production support, observability, and Agile delivery. The engineer collaborates with engineering, product, testing, release, and application support teams to deliver resilient, high-volume transaction-processing solutions.

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.

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.

Manage multi-region AWS infrastructure and Linux servers, including configuration, migrations, upgrades, patching, monitoring, access control, troubleshooting, and root-cause analysis. Support serverless and container infrastructure, analyze logs and performance trends, audit infrastructure, mitigate threats, and resolve escalated operational issues. Mentor new team members and collaborate in a hybrid, client-facing consulting environment.

Lead Java backend modernization and Kubernetes migration initiatives. Design and develop resilient microservices, REST APIs, integrations, and deployment strategies. Provide technical leadership, conduct design and code reviews, oversee CI/CD and containerized deployments, coordinate regional releases, optimize performance, manage observability, and troubleshoot production issues while ensuring secure coding, testing, and engineering standards.

Build and maintain reliable, scalable Java and Go backend microservices for a cloud-native SaaS identity analytics product. Responsibilities include designing APIs, implementing features, writing unit and end-to-end tests, conducting code reviews, supporting AWS infrastructure, collaborating with stakeholders, leading small projects, participating in on-call support, and troubleshooting escalated system issues.

Design and build data services and pipelines supporting machine learning products. Develop automation tools for model deployment, maintain production data systems, improve infrastructure, participate in code reviews, and collaborate across engineering, data science, and product teams. The role requires expertise in distributed systems, large-scale data processing, CI/CD, container orchestration, and AI-enabled workflow improvements.

Lead development of high-performance Java backend services for Mastercard’s fraud decision-management platform. Responsibilities include system design, production development, code and security reviews, CI/CD and cloud-native delivery, production support, SDLC documentation, vendor and offshore coordination, technical training, mentoring, and Agile SAFe participation. The role also drives engineering standards, technology evaluations, performance benchmarking, deployment planning, and secure coding practices.

Leads the architecture and delivery of enterprise backend services, APIs, distributed systems, cloud-native platforms, AI-enabled workflows, and data solutions. Defines technical standards and roadmaps, drives modernization and automation, and ensures reliability, security, observability, and performance. Mentors engineers, supports hiring and development, leads incident response, and collaborates across product, architecture, security, and operations teams to advance platform strategy and engineering excellence.