Top AWS Jobs in Bangalore

Develops secure, scalable Java full-stack applications for payments technology. Responsibilities include system design, production coding, testing, troubleshooting, architecture documentation, data analysis, operational stability, and participation in engineering communities. The role uses Java EE, Spring Boot, messaging systems, databases, containers, testing frameworks, cloud technologies, React, and AI-assisted development tools while following secure and responsible AI practices.

Design, deploy, integrate, upgrade, and troubleshoot cloud-native network functions in Cloud NFVI environments. Configure Kubernetes-based platforms and hybrid Azure/AWS infrastructure, manage C-NeLS licensing solutions, execute testing and migration activities, validate deployment scripts, resolve customer service requests, and perform root cause analysis. The role also requires stakeholder communication, automation, configuration management, and adherence to operational, legal, and safety standards.

Design and develop scalable backend microservices for enterprise travel policies, approval workflows, compliance, data processing, reporting, and integrations. Own systems end to end, define technical roadmaps, improve reliability and performance, collaborate cross-functionally, and mentor engineers. The role requires expertise in Java, Spring Boot, distributed systems, databases, cloud platforms, testing, monitoring, and data integrity, with bonus experience in AI/ML, data pipelines, and travel technology.

Build and maintain core infrastructure services and distributed microservices supporting machine learning, frontend, and platform teams. Develop capabilities including configuration management, rate limiting, feature flags, A/B testing, and traffic capture and replay. Improve cloud infrastructure performance, scalability, latency, and observability. Own features end-to-end, deliver deadline-sensitive work, collaborate across engineering teams, and influence the infrastructure roadmap.

Lead and grow a multi-pod engineering team building Atlassian’s JSM analytics platform. Own technical direction and delivery for custom metrics, insights, operations and assets reporting, spanning React frontends, GraphQL APIs, distributed data pipelines and cloud infrastructure. Drive products from early access through general availability while improving scale, performance, data quality and observability. Hire, coach and retain senior engineers and deliver analytics capabilities for enterprise customers.

Leads the design, development, and operation of enterprise data platforms using Java, Python, cloud-native architectures, and big-data technologies. Drives SRE practices, observability, automation, incident response, resilience, and secure production delivery. Leads adoption of AI-assisted engineering tools, defines governance and quality controls, establishes SLOs and SLIs, mentors engineers, conducts root-cause analysis, and influences architecture across multiple teams.

Leads architecture and implementation of secure, scalable data and integration solutions using Java, Kafka, AWS, Cassandra, Oracle, REST, and GraphQL. Designs streaming and batch pipelines, data contracts, APIs, distributed systems, observability, and governance patterns. Drives proof-of-concepts, production readiness, AI-assisted engineering practices, secure coding, testing, and cross-team technical standards. Requires strong technical leadership, stakeholder communication, and experience operating large-scale production systems.

Provides second-level support for network incidents, problems, and technical operations. Maintains and troubleshoots routers, switches, firewalls, proxies, load balancers, wireless networks, DNS, and email security systems. Identifies network improvements, redesigns alarms, supports cloud networking across Azure, AWS, GCP, and IBM Cloud, and contributes to automation and documentation. Requires 24x7 on-call flexibility, strong Cisco and Juniper expertise, and hands-on experience with routing, security, cloud, DevOps, and infrastructure technologies.

Design, build, and operate high-throughput backend services for forecasting, recommendations, and AI-driven decisioning. Own services from architecture through deployment and incident resolution, using distributed systems, APIs, event-driven pipelines, cloud infrastructure, and machine-learning integrations. Improve scalability, reliability, observability, and performance while collaborating with data science, platform, and product teams. Mentor engineers and contribute to design reviews, production support, and systemic improvements.

Provides hands-on technical leadership for forecasting, recommendation, and agentic AI platforms. Designs, builds, and operates high-throughput, low-latency distributed systems, APIs, data pipelines, model inference services, and agent orchestration. Owns services through production operations, on-call response, observability, incident resolution, scalability improvements, and architectural reviews. Guides cross-team technical direction and delivers reliable cloud-native systems across AWS and on-premises environments.

Build and own backend components for high-volume endpoint data pipelines, from requirements and design through deployment. Develop Java microservices and event-driven distributed systems using Kafka, Kafka Streams, Spring Boot or Micronaut, SQL, and AWS. Apply concurrency, automated testing, observability, CI/CD, and DevOps practices while collaborating with Endpoint and Product teams to deliver scalable cloud-platform features.

Leads global production management and technology support teams responsible for service availability, resiliency, performance, security, and operational excellence. Establishes SRE practices, observability standards, incident governance, automation, CI/CD, disaster recovery, and AWS resiliency strategies. Oversees major incident response, root-cause remediation, IAM controls, compliance evidence, capacity planning, and executive reporting. Partners across engineering, security, infrastructure, and business teams while governing safe, auditable AI use in production support workflows.

Leads the design, development, and evolution of a scalable CI/CD platform. Writes, reviews, tests, debugs, and operationalizes secure production software while guiding architecture and technical decisions. Champions AI-assisted engineering practices with validation for correctness, performance, security, and responsible use. Serves as a subject matter expert, coaches engineers, and promotes enterprise software development frameworks, automation, resiliency, and cloud-native practices.

Develop scalable full-stack applications using Angular, TypeScript, Java, Spring Boot, and microservices. Build responsive accessible interfaces, reusable design systems, REST APIs, and backend services integrated with enterprise platforms. Optimize performance, security, scalability, databases, and automated testing. Collaborate with product, UX, QA, platform, and engineering teams while applying CI/CD, DevOps, Git workflows, and AI-assisted development tools.

Develops, tests, troubleshoots, and maintains secure, scalable software within an agile Asset and Wealth Management team. Writes Python or Java code, works with databases and large datasets, supports application resiliency and security, and participates across the software development lifecycle. Uses enterprise-authorized AI-assisted development tools responsibly for coding, testing, troubleshooting, and documentation. Preferred experience includes high-performance Python, Redis, Kafka, specialized time-series databases, and AWS.

Architects, develops, and scales secure cloud-native software, microservices, distributed systems, and REST/gRPC APIs. Leads end-to-end technical execution, mentors engineers, collaborates with frontend teams, monitors system health, troubleshoots issues, and optimizes services. The role requires expertise in Java, Spring, containers, cloud platforms, observability, SDLC practices, and high-availability architecture, with preferred experience in AI security, threat intelligence, disaster recovery, TDD, Agile, and CI/CD.

Lead a team of 4–6 software engineers in delivering Detection Engineering and SOC Workbench roadmaps. Drive technical excellence, reliable microservices, distributed security platforms, system performance, troubleshooting, optimization, and operational reliability. Manage direct reports’ performance and career progression while aligning engineering execution with organizational goals. The role requires extensive engineering leadership, security platform experience, cloud architecture knowledge, and familiarity with AI/ML, multi-language development ecosystems, DevOps, CI/CD, and automation.

Leads development of scalable, resilient, cloud-native backend systems using Java, Spring Boot, Kubernetes, and AWS. Designs, tests, reviews, debugs, and operates secure production software while improving automation and operational stability. Drives architecture evaluations, software engineering communities of practice, and responsible adoption of AI-assisted development tools. Coaches teams on secure coding, validation, resiliency, CI/CD, and enterprise software delivery practices.

Lead the technical vision, architecture, and delivery of Atlassian’s large-scale Search Platform. Responsibilities include building distributed ingestion and indexing systems, supporting multi-cloud and isolated-cloud environments, meeting enterprise compliance and encryption requirements, improving throughput and reliability, optimizing infrastructure costs, and advancing vector, hybrid, and agentic retrieval capabilities. The role requires cross-functional technical leadership across ML, data, cloud infrastructure, and product teams.

Provides second-level support for network incidents, problem resolution, and technical operations. Maintains and optimizes routers, switches, firewalls, proxies, load balancers, DNS, wireless infrastructure, and security solutions. Investigates problems, implements workarounds, improves deployed solutions, redesigns network alarms, documents procedures, and supports cloud networking across Azure, AWS, GCP, and IBM Cloud. The role requires hands-on troubleshooting, automation, stakeholder communication, and flexible 24x7 on-call support.

Lead a team delivering DevOps automation and solutions for Ericsson’s 4G and 5G customer environments. Responsibilities include performance monitoring, troubleshooting, platform management, system design, CI/CD automation, infrastructure and service lifecycle management, reliability improvements, customer deployments, and operational support. The role requires building scalable cloud-native systems, maintaining DevOps platforms, automating deployment of numerous services, and collaborating with development teams on testing, releases, security, and compliance.

Leads software engineering teams and technical projects, designing, developing, testing, deploying, and supporting distributed full-stack systems. Responsibilities include microservices, databases, AWS serverless technologies, build and deployment pipelines, architecture patterns, troubleshooting, data correction, user experience enhancements, mentoring, and technical direction. The role requires extensive backend development, distributed systems, database, cloud, testing, and technical leadership experience.

Design and build scalable web applications on AWS using React, TypeScript, Python, and DevOps practices. Ensure code quality through Agile/Scrum delivery, unit and integration testing, code reviews, documentation, and engineering design specifications. Optimize application performance, database queries, caching, response times, logging, and troubleshooting while applying security fundamentals and enabling CI/CD.

Design, build, test, deploy, and maintain distributed software systems using modern engineering practices. Collaborate with AI Studio teams and engineering leaders to solve business problems, improve performance, reliability, cost, and security, and deliver scalable service-oriented applications. Conduct code reviews, mentor junior engineers, and contribute across the full software development lifecycle, including architecture, testing, operations, and cloud deployment.

Develops secure, scalable software for AI/ML and generative AI platforms within an agile team. Responsibilities include Python and AWS development, platform engineering, MLOps, data governance, LLM fine-tuning, multi-agent orchestration, troubleshooting, automation, continuous integration, and communicating technical solutions across the organization.