Top AWS Jobs in Pune

Develops, tests, maintains, and optimizes enterprise Oracle database applications using SQL and PL/SQL. Responsibilities include building database objects, performance tuning, troubleshooting production issues, supporting deployments, documenting solutions, and collaborating with cross-functional teams. Lead-level duties include mentoring developers and enforcing development standards. The role requires at least five years of experience and familiarity with Agile/Scrum, version control, production support, and database design.

Develop scalable, high-throughput software solutions for Barclays by analyzing business requirements, designing services and processes, collaborating with stakeholders, and supporting delivery and change management. Build Java and Spring Boot microservices using REST APIs, Kafka, SQL Server, cloud platforms, containers, and CI/CD. Contribute to architecture, observability, risk controls, root-cause analysis, and continuous service improvement while guiding stakeholders and team members.

Designs and executes comprehensive software testing strategies, develops automated test scripts, validates APIs, databases, cloud platforms, performance, and end-to-end functionality, and performs defect analysis. The role supports CI/CD integration, test framework enhancement, Agile ceremonies, sprint planning, stakeholder communication, risk management, and continuous quality improvement. It also requires collaboration with developers, product owners, and QA teams to deliver reliable software across complex systems.

Develop end-to-end full stack features using Java and Apache Kafka, covering user experience through backend services. Collaborate across teams, make technical decisions, mentor junior engineers, solve complex business problems, and improve development processes. The role requires RESTful API development, cloud technologies, front-end frameworks, and SQL or NoSQL database experience within a cloud-first, agile environment.

Develop and maintain end-to-end full-stack features using Java, front-end frameworks, RESTful APIs, databases, and Apache Kafka. Collaborate across teams, make technical decisions, mentor junior engineers, provide solutions, and continuously improve development processes using cloud-first and agile practices.

Develop end-to-end full-stack features using Java, Apache Kafka, RESTful APIs, cloud technologies, frontend frameworks, and SQL/NoSQL databases. Collaborate across teams, make technical decisions, mentor junior engineers, act as a subject matter expert, and continuously improve development processes within a cloud-first, agile environment.

Develop and engineer end-to-end system features spanning user experience and backend services. The role involves Java full-stack development, Apache Kafka, RESTful APIs, cloud technologies, databases, and front-end frameworks. Responsibilities include collaborating across teams, making technical decisions, mentoring junior engineers, serving as a subject matter expert, and improving development processes within an agile, cloud-first environment.

Designs, develops, and deploys autonomous and multi-agent AI systems for business workflows. Builds agentic applications using LLMs, RAG, vector databases, tool calling, memory, and orchestration frameworks. Integrates agents with enterprise applications, APIs, databases, CRMs, and ERPs while developing backend services and APIs. Optimizes solutions for scalability, security, performance, and cost, and collaborates with product, engineering, and business teams to identify automation opportunities.

Supports, monitors, troubleshoots, deploys, and enhances integrated enterprise applications. Responsibilities include incident resolution, log analysis, batch processing oversight, database refreshes, integration validation, application resiliency, SQL-based data analysis, documentation, and coordination with business, development, infrastructure, and cybersecurity teams.

Monitor, investigate, and respond to cybersecurity events across a global enterprise. Responsibilities include SIEM monitoring, threat hunting, incident response, endpoint and email threat analysis, DLP investigations, firewall policy review, vulnerability assessments, SOC documentation, and playbook development. The role also mentors junior analysts and serves as a senior escalation point during shift operations.

Supports and maintains privileged access management infrastructure using CyberArk, BeyondTrust, and HashiCorp Vault. Responsibilities include platform monitoring, upgrades, integrations, automation, credential rotation, access governance, troubleshooting, incident resolution, documentation, and audit compliance. The role integrates PAM solutions with enterprise applications, Kubernetes, cloud platforms, and CI/CD pipelines while partnering with global security, infrastructure, DevOps, and application teams.

Support data governance policy implementation, data discovery, classification, cataloging, quality monitoring, metadata and lineage documentation, risk assessments, audits, tool administration, and remediation. Partner with data owners, stewards, and IT teams to promote secure, compliant, and trusted data. Provide training, user support, workflow assistance, and governance dashboards for leadership.

Leads the Infrastructure Platform Engineering team within a global SRE organization. Responsibilities include people management, hiring, prioritization, operational excellence, incident response, reliability improvements, and cross-functional coordination. The role requires technical depth in Kubernetes, containerized platforms, public cloud, observability, infrastructure as code, CI/CD, and automation, along with experience managing distributed engineering teams supporting business-critical production systems.

Lead the design, development, deployment, and optimization of production-grade Generative AI systems. Build RAG pipelines, fine-tune foundation models, develop AI agents, establish evaluation and observability frameworks, and integrate multimodal AI capabilities. Collaborate with product, engineering, data, and business stakeholders to deliver scalable, reliable, secure, and responsible AI solutions.

Designs and maintains data foundations, pipelines, ETL/ELT processes, integrations, and data models across cloud platforms. Ensures data quality, supports data strategy implementation, coordinates change and incident management, presents findings to stakeholders, and mentors engineers. The role partners with technical and business teams to improve data accessibility, implementation efficiency, and business value.

Leads advanced research and development in industrial digital twins, simulation, robotics, computer vision, and industrial AI. Designs scalable models and prototypes for manufacturing, process optimization, predictive maintenance, and autonomous systems. Collaborates with technology partners, academic institutions, architects, engineers, and industry experts. Provides technical leadership, mentors teams, drives innovation roadmaps, publishes research, contributes to patents, and leads proofs of concept and pilot implementations.

Administer, support, and engineer enterprise DevOps platforms, CI/CD pipelines, artifact repositories, source control, deployment tooling, and Kubernetes environments. Troubleshoot pipeline, access, agent, integration, and deployment issues; automate platform administration; manage security controls, credentials, and secrets; develop reusable pipelines and GitOps workflows; monitor reliability and performance; support incident response, documentation, high availability, backup, disaster recovery, and developer self-service.

Administer and maintain enterprise VMware, Windows, and Linux infrastructure. Responsibilities include monitoring, troubleshooting, VM provisioning and lifecycle management, patching, security remediation, PowerShell and PowerCLI automation, and support for hybrid cloud and Cisco UCS environments. The role also involves ServiceNow ticket resolution, documentation, incident and change processes, collaboration with technical teams, and participation in on-call and maintenance activities.

Senior technical leader responsible for engineering strategy, platform-scale architecture, and delivery across multiple teams. Owns technical roadmap for shared services, champions event-driven architectures (Kafka), provides hands-on guidance for Java microservices, ensures reliability, observability, and security, and partners with senior business and technology stakeholders to drive execution and scalability.

Lead delivery of cloud data platform solutions: design and build pipelines on Snowflake/Databricks using SQL, PySpark and ETL tools, implement CI/CD, work client-facing to run workshops, mentor junior staff, and identify business value.

Leads end-to-end architecture for Java and Spring Boot microservices, full-stack applications, and cloud-native platforms. Drives modernization, cloud migration, event-driven design, and AI integration across Azure or AWS environments. Defines architecture deliverables, ensures scalability, security, resilience, and compliance, collaborates with product and engineering stakeholders, and mentors senior engineers.

Supports production AI platforms by monitoring service health, triaging incidents, conducting root-cause analysis, and maintaining post-incident reviews. Builds observability dashboards, alerts, logging, deployment pipelines, vector database and ingestion workflows, automation, and runbooks for LLM workloads. Serves as an escalation point, supports onboarding, and collaborates with engineering and product teams to improve platform reliability and user experience.

Lead engineering teams to deliver high-quality software by providing technical guidance, mentoring, overseeing delivery timelines, improving processes and tooling, enforcing standards, and collaborating with product and stakeholders. Drive DevOps/CICD, cloud, containerization, IaC, code quality and automation practices within the Mortgages digital domain.

Build and maintain scalable AWS data platforms, including batch and streaming ETL/ELT pipelines, data lakes, warehouses, and analytics-ready data models. Develop SQL transformations and Python-based pipelines using AWS services such as S3, Glue, EMR, Redshift, and Athena. Monitor performance, reliability, and data quality; troubleshoot issues; apply security and scalability practices; and collaborate with architects, DevOps, QA, product teams, and business stakeholders.

Build and maintain scalable AWS data platforms and batch or streaming pipelines. Develop SQL transformations and Python ETL workflows using services such as S3, Glue, EMR, Athena, and Redshift. Design data lakes, warehouses, and analytics-optimized models while monitoring performance, reliability, security, and data quality. Troubleshoot pipeline issues, support deployments, and collaborate with architects, DevOps, QA, product teams, and business stakeholders.