Top AWS Jobs in Pune

Develops and maintains data engineering solutions involving ingestion, aggregation, processing, curation, modeling, and analysis of high-volume data. Uses Cloudera, Databricks, AWS, Python, PySpark, SQL, and related tools to unify data assets, generate insights, support business intelligence, and enable fraud, security, and digital identity products. Partners with product, data science, platform, technology, client, and sales teams to deliver data solutions, prototypes, and enhancements.

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 and deploys generative AI and machine learning solutions for AML transaction monitoring. Builds RAG, MCP, tool-calling, LLM fine-tuning, multimodal content generation, computer vision, evaluation, observability, and MLOps systems. Develops scalable cloud solutions using AWS, Azure, and Databricks, integrates models into production applications, and ensures performance, security, and compliance. Collaborates with technical and business stakeholders while applying current AI/ML research.

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.

Own the strategy, roadmap, requirements, and delivery of AI-powered financial reconciliation products. Lead discovery with financial stakeholders, translate reconciliation and regulatory needs into BRDs, epics, and user stories, prioritize backlogs, and guide engineering and AI/ML teams from concept through launch. Define performance KPIs, support pricing and go-to-market activities, and ensure compliance, governance, auditability, and financial controls across enterprise reconciliation workflows.

Lead the design and development of scalable cloud-native data platforms and batch or real-time pipelines supporting AI, machine learning, and Generative AI. Build infrastructure for feature engineering, model training, inference, LLMs, RAG, embeddings, and vector databases. Ensure data quality, governance, security, observability, reliability, and cost efficiency while enabling MLOps and AgenticOps capabilities across enterprise AI initiatives.

Supports the design, requirements, testing, documentation, and delivery of AI-powered and API-enabled financial reconciliation products. Maintains backlogs, coordinates agile execution, analyzes API telemetry and product metrics, supports AI feature evaluation, and documents controls for agentic workflows. Collaborates with engineering, operations, finance, compliance, and business stakeholders on discovery, integrations, client onboarding, go-to-market materials, roadmap planning, and leadership reviews.

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.

Lead the architecture, development, scaling, and modernization of Java-based AWS microservices and full-stack web interfaces. Build RESTful APIs, responsive UIs, automated testing pipelines, telemetry, and continuous delivery workflows. Optimize distributed systems for resilience, scale, and low latency while driving architecture discussions, code reviews, technical sizing, and mentorship across the engineering organization.

Lead design and delivery of modern, secure, scalable cloud-native data platforms (Lakehouse) across AWS and Azure. Drive DevOps/IaC, data governance, medallion architecture, performance and cost optimization, mentor global engineers, and collaborate with stakeholders to translate business requirements into production data solutions.

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.

Designs, develops, tests, deploys, and operates secure, mission-critical software for Mastercard’s VCN, Spend Controls and Alerts team. Partners with product and business stakeholders to prioritize work, integrate services, improve customer journeys, manage risks, and optimize delivery and operational metrics. Responsibilities include architecture, debugging, CI/CD automation, API development, quality scanning, performance and security requirements, release testing, product demos, incident mitigation, and mentoring less-experienced engineers.

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.

Develop and deploy generative AI solutions for anti-money laundering transaction monitoring. Build RAG, MCP, tool-calling, LangChain, LangGraph, LLM fine-tuning, multimodal generation, computer vision, evaluation, observability, and MLOps systems. Deploy scalable AI applications on AWS, Azure, and Databricks while ensuring performance, security, and compliance. Collaborate with technical and non-technical stakeholders and apply current AI/ML research to real-world problems.

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.

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.

Lead and grow agile engineering teams to design, build, and operate large-scale, distributed payment systems. Provide hands-on technical leadership across architecture, code quality, testing, CI/CD, security, and cloud-native deployments while partnering with product and program teams to ensure predictable, high-quality delivery.

Design, build, automate, and optimize Mastercard/Vocalink's Windows platform using SCCM, Ansible, and IaC. Implement automated OS deployment, patching, compliance, and build pipelines; integrate with CI/CD and Git workflows. Lead platform modernization, troubleshoot complex Windows issues, and collaborate with security, infrastructure, application teams and vendors to deliver scalable, secure platform services.

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.

Leads hands-on design, development, testing, documentation, deployment, and support of secure, scalable Java backend and microservices solutions. Collaborates with architecture, product, security, platform, QA, and cross-functional Agile teams; drives technical decisions, code quality, testing coverage, production support, root-cause analysis, and continuous improvement. Mentors junior engineers and contributes to engineering standards and knowledge sharing.

Administer and support AWS cloud and Windows Server environments, including monitoring, patching, vulnerability remediation, security hardening, troubleshooting, root cause analysis, automation with PowerShell, documentation, and infrastructure modernization or migration initiatives.

Develop, test, implement, document, maintain, and support secure, scalable software applications. Build API and UI test automation, validate system integrations, implement CI/CD quality gates, refactor automation code, and follow software quality and security standards. Collaborate with cross-functional Agile teams, meet delivery timelines, report project metrics, identify emerging issues, and recommend solutions.

Leads and manages software engineering teams developing scalable Java, cloud, and microservices-based products and platforms. Responsibilities include architecture leadership, hands-on development, code reviews, technical design, agile delivery, engineering quality, cloud enablement, streaming analytics, recruiting, mentoring, and stakeholder collaboration. The role oversees the full software development lifecycle and advances high-volume data access, platform strategy, and engineering productivity.

Leads the design, development, and delivery of scalable full-stack Java applications using React or Angular. Establishes architecture, technical standards, APIs, microservices, security, resiliency, and zero-downtime production practices. Collaborates with product and cross-functional teams, provides technical leadership, estimates scope and timelines, and supports project delivery. The role also drives cloud-native development, DevOps automation, observability, release management, and adoption of generative AI solutions.