Top AWS Jobs in Pune

Leads the design and development of Chef-based automation frameworks, configuration management, and platform services for hybrid infrastructure. Builds reusable Infrastructure as Code and CI/CD integrations, automated testing, compliance controls, self-service capabilities, and GitOps workflows. Collaborates with cloud, platform, and security teams to enforce hardened configuration baselines, troubleshoot complex infrastructure issues, and improve observability and operational tooling.

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.

Develop generative AI and machine learning solutions for anti-money-laundering transaction monitoring. Responsibilities include building RAG and agentic workflows, fine-tuning foundation models, creating multimodal and computer vision applications, evaluating model quality and bias, implementing AI observability, and deploying secure, scalable systems on cloud and data platforms. The role also contributes to MLOps, production integration, research adoption, and collaboration with technical and non-technical stakeholders.

Designs, builds, secures, and governs enterprise APIs and cloud-native microservices using Java, Spring Boot, Python, and AWS. Defines API standards, OpenAPI specifications, security practices, testing strategies, and distributed-system patterns. Develops reusable frameworks, SDKs, and platform capabilities while collaborating with product, architecture, security, and engineering teams. Contributes to code reviews, incident resolution, modernization, automation, and long-term API architecture strategy.

Own the strategy, roadmap, lifecycle, and execution of Mastercard’s Data and AI platform. Partner with engineering, security, compliance, legal, vendors, and stakeholders to define requirements, prioritize features, address performance challenges, and drive adoption and revenue. The role requires experience with SaaS data platforms, cloud and on-premises storage, multi-tenant architectures, AI/ML technologies, Agile product ownership, and enterprise platform development.

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.

Supports technical project delivery through requirements gathering, functional and technical specifications, system behavior definition, API and data modeling, integration analysis, gap analysis, testing documentation, and application troubleshooting. Collaborates with stakeholders, development teams, vendors, and business owners to translate business needs into implementable solutions. The role also supports risk management, incident management, Agile delivery, and reliable operation of enterprise systems.

Leads and mentors software engineering teams developing scalable Java applications and microservices for high-volume card payment platforms. Owns architecture, design quality, cloud modernization, Agile delivery, operational excellence, security, and production reliability. Manages hiring, performance, career development, risks, dependencies, and cross-functional coordination while solving complex payment processing and settlement issues.

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.

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.

Leads architecture and technical direction for Mastercard’s global-scale merchant acceptance platform. Designs resilient, high-availability microservices, APIs, cloud-native systems, and technical blueprints for high-volume payment environments. Partners with product, architecture, operations, and engineering teams; reviews implementations; mentors technical staff; and prototypes solutions. Requires extensive experience with Java, Spring, Kubernetes, cloud platforms, databases, continuous delivery, and financial systems operating at global scale.

Design, build, and deploy AI and Generative AI solutions using LLMs, agent frameworks, and RAG. Develop scalable AI/ML pipelines, cloud-native integrations (Azure/Databricks/AWS), and MLOps/LLMOps deployments. Integrate AI with APIs, databases, and internal apps. Implement Responsible AI practices (bias detection, hallucination mitigation, explainability, safety guardrails). Monitor, test, and maintain production AI systems while staying current on Generative AI trends.

Designs, builds, and operates Mastercard’s enterprise Developer Workbench platform. Responsibilities include integrating developer tools, managing tooling lifecycles, creating standardized onboarding environments, advancing AI-assisted development capabilities, implementing CI/CD and cloud-native solutions, measuring developer productivity, and ensuring security and regulatory compliance. The role collaborates across product, platform, security, compliance, and engineering teams while contributing to technical strategy and engineering standards.

Build and improve production-oriented enterprise AI solutions using prompts, LLMs, RAG, workflow automation, APIs, governed data, and evaluation frameworks. Integrate systems such as Salesforce, Slack, Snowflake, and AWS using n8n, Python, JavaScript, or TypeScript. Apply context engineering, observability, security, privacy, testing, and reliability controls while partnering with business, product, data, security, and engineering stakeholders.

Build and operate a self-service data commercialization platform spanning web experiences, APIs, cloud infrastructure, lakehouse systems, and automation. Develop scalable data platforms using Python, Spark, Databricks, orchestration, Java, React, and cloud services. Design secure, reliable workflows with observability, access controls, infrastructure as code, CI/CD, and multi-cloud architecture. Collaborate on technical trade-offs and integrate distributed systems, databases, and AI-powered capabilities.

Leads the architecture, design, coding, testing, and delivery of scalable, secure, cloud-native software and data distribution platforms. Defines modernization strategy, builds APIs, services, data pipelines, and analytical capabilities, and drives architecture and design reviews. Coordinates globally distributed teams, partners across engineering and business functions, mentors engineers, and promotes reliability, observability, continuous delivery, and engineering excellence.

Build and operate scalable cloud data and lakehouse platforms, including self-service interfaces, automation, APIs, infrastructure, governance, and security. Develop backend services with Java and Spring Boot, web experiences with React and TypeScript, and data solutions using Python, Spark, Databricks, and orchestration tools. Design reliable workflows, distributed systems, integrations, and cloud infrastructure across AWS and/or Azure. Contribute to architecture, observability, testing, cost optimization, and AI-powered platform capabilities.

Design and implement production-grade AI and machine learning solutions, including scalable GenAI applications, RAG pipelines, ML platforms, data pipelines, and distributed cloud systems. Collaborate with architects and client-facing teams, write tested and maintainable code, conduct technical research and proofs of concept, participate in Agile delivery, troubleshoot production issues, review code, estimate work, and mentor engineers.

Drive enterprise software acquisition and revenue growth across a regional territory. Manage prospects and a small existing customer base using land-and-expand strategies, executive engagement, demonstrations, events, territory planning, and strategic account development. Build relationships with VP and C-level stakeholders, partners, and internal teams to close complex sales, acquire new logos, expand usage, and support successful customer implementations.

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 enterprise applications, optimize transactional data models and queries, integrate with existing workflows, and collaborate with developers, analysts, QA, and operations teams.

Build and maintain reliable, scalable Java-based microservices for SailPoint’s cloud identity analytics SaaS product. Responsibilities include technical design, feature implementation, code reviews, testing, production performance instrumentation, CI/CD improvements, and collaboration across an agile engineering team. The role will eventually own functional areas, contribute to architecture decisions, and lead scalable microservice enhancements.

Build and scale machine learning systems for search, including ranking models, feature engineering, model deployment, monitoring, experimentation, and online inference. Design fault-tolerant distributed infrastructure, optimize search latency and throughput, and develop reliable ML services from proof of concept through production. Collaborate across engineering and product teams, communicate technical decisions, review code, document systems, and mentor junior engineers.

Leads the design, development, deployment, and support of scalable data pipelines and platforms across Hadoop, on-premises, and AWS cloud environments. Builds batch and near-real-time processing frameworks, modernizes ETL and data warehouse workloads, implements governance and observability capabilities, and troubleshoots production issues. Mentors engineers, collaborates with cross-functional stakeholders, evaluates emerging technologies, and ensures secure, high-quality delivery for enterprise-scale data ecosystems.

Leads and mentors a software engineering team developing SailPoint’s cloud-native identity security products. Responsibilities include writing and reviewing code, debugging distributed systems, managing Agile delivery, planning projects, coordinating with global stakeholders, improving architecture and processes, managing technical risks, and delivering AWS-based microservices and product features.

Develop and maintain full-stack software and platform solutions for disability and absence products. Responsibilities include designing systems, frameworks, applications, APIs, and databases; developing with React or Angular, Java, SQL, microservices, Kubernetes, and cloud platforms; participating in code reviews, testing, deployment, incident resolution, production support, Agile planning, and user-story refinement.