Top AWS Jobs in Bengaluru

Lead the design and implementation of scalable software systems across Built In’s product lines. Drive technical features, improvements, AI-enabled capabilities, and end-to-end software development on public cloud platforms. Analyze system-level issues, implement solutions, collaborate across product and technology teams, and mentor engineers while promoting agile development, observability, continuous delivery, and engineering excellence.

Design and ship full-stack asset lifecycle management systems for solar and battery assets. Build Kotlin and Spring Boot services, client-facing onboarding APIs, configurable validation engines, and React/TypeScript tools. Maintain data integrity across platforms, perform migrations and backfills, support production services, and improve monitoring and alerting. Lead technical design discussions, conduct code reviews, mentor engineers, collaborate with product and operations teams, and use AI tools to accelerate coding and testing.

Owns product features end to end across backend, frontend, mobile, infrastructure, and production operations. Builds AI agents and automated healthcare workflows, designs services and APIs, manages infrastructure, writes model evaluations, monitors production systems, and handles incidents. The role requires strong Python and TypeScript full-stack skills, hands-on AI harness experience, daily use of coding agents, product judgment, and the ability to independently take ambiguous problems from concept to deployment.

Build and own full-stack healthcare platform features from concept through production. Responsibilities include developing AI agents and automated workflows, web and mobile experiences, APIs, data models, infrastructure as code, monitoring, incident response, model evaluations, and secure PHI handling. The role requires strong Python and TypeScript skills, hands-on AI harness experience, daily use of coding agents, product judgment, and end-to-end ownership in a distributed engineering team.

Build and scale high-performance backend services for a real-time threat intelligence platform. Develop low-latency streaming architectures, optimize OpenSearch or Elasticsearch indexing, manage AWS/EKS deployments, and translate broad goals into technical specifications and maintainable code. Collaborate with teammates to identify architectural gaps and improve systems. The role requires production backend experience with Python or Golang, Kafka or Kinesis, search platforms, Kubernetes, AWS, and PostgreSQL.

Leads DevOps, SRE, DevSecOps, and platform reliability across Azure and AWS. Owns Kubernetes infrastructure, CI/CD, GitOps, databases, observability, security, distributed systems, incident response, disaster recovery, and FinOps. Builds and mentors engineering teams while improving availability, deployment safety, MTTR, DORA metrics, compliance, and cloud cost efficiency. This hands-on leadership role requires deep cloud-native, infrastructure, automation, and production troubleshooting expertise.

Build and operate secure, reliable cloud-native deployments for a healthcare SaaS platform. Own CI/CD pipelines, GitOps workflows, Kubernetes deployments, Azure infrastructure, infrastructure-as-code, observability, database operations, security automation, and cloud cost optimization. Troubleshoot production systems, participate in on-call rotations, improve deployment and recovery processes, and reduce operational toil through automation.

Own the architecture, roadmap, performance, reliability, security, and scalability of Albert’s Node.js API platform and backend infrastructure. Lead platform transition initiatives, distributed systems design, authorization frameworks, event-driven architecture, observability, infrastructure as code, and CI/CD. Establish engineering standards and AI-native development practices while managing and mentoring a team of platform engineers and influencing product, security, and technical leadership.

Own the architecture and technical direction of regulatory data systems, including safety data sheet generation, rule engines, substance data, and regulatory integrations. Build scalable backend services with Node.js, TypeScript, and AWS, develop agentic data workflows, lead technical specifications and architectural decisions, manage regulatory scoping and execution, establish engineering standards, and mentor senior engineers.

Own end-to-end quality for web platforms and mobile apps by writing test cases, building automated regression suites, evaluating AI-powered testing tools, validating data and user journeys, and supporting releases. The role includes bug reporting, production investigation, customer-facing technical support, documentation, and collaboration with engineers to verify fixes. The engineer will work with Playwright, Cypress, Selenium, and AI tools while developing broader engineering skills.

Own the architecture, reliability, freshness, quality, and cost of CertifyOS’s data platform. Lead engineers delivering distributed batch and real-time pipelines, OLTP, OLAP, and NoSQL systems; drive entity resolution and master data management; build data products and ML foundations; improve scale and performance; establish observability and SLAs; mentor engineers; and participate in on-call incident response.

Build AI-assisted quality engineering workflows, scalable UI/API/integration and end-to-end automation, performance and load tests, and reliability checks. Integrate automated testing into CI/CD pipelines, establish quality gates, analyze failures and bottlenecks, and validate distributed systems, databases, asynchronous workflows, and recovery behavior. Collaborate with engineering and product teams to improve test coverage, scalability, release confidence, and development productivity.

As a Forward Deployed Engineer, you will design, build, and deploy AI agents, integrating them with external systems, optimizing performance, and advising customers on AI architecture and scalability.

Lead the architecture and evolution of Albert OS data platforms, including lakehouse infrastructure, analytical pipelines, transactional systems, and batch and streaming ingestion. Define data modeling standards, optimize SQL and NoSQL performance, establish data security and observability practices, and collaborate with API and Data Science teams on shared data contracts. Mentor engineers and guide cross-functional architectural decisions.

Architects and operates scalable cloud and on-premise infrastructure, CI/CD pipelines, Kubernetes platforms, and infrastructure-as-code workflows. The role focuses on automation, system availability, security, performance, incident response, troubleshooting, monitoring, and operational efficiency. The engineer collaborates across engineering, security, and product teams, prototypes emerging technologies, supports production systems, and drives root-cause analysis and continuous improvement.

Build and manage observability solutions using Datadog and Splunk across applications, cloud infrastructure, APIs, and Kubernetes. Develop dashboards, alerts, reports, SPL queries, and distributed tracing capabilities. Troubleshoot production incidents, conduct root cause analysis, and improve system reliability in collaboration with DevOps, SRE, application, and infrastructure teams. Automate monitoring tasks using Python, Bash, and Terraform.

Maintain client relationships and technical support throughout the build, deployment, and ongoing lifecycle. Administer Linux systems, Kubernetes, Docker, AWS environments, CI/CD pipelines, and distributed applications. Troubleshoot Java servers, Nginx, APIs, storage, and infrastructure incidents. Create technical documentation, manage tickets, resolve problems promptly, and collaborate with teams while adapting to evolving technologies.

Build and operate secure, scalable backend services and data ingestion pipelines. Own features from design through production, develop third-party API integrations, improve data freshness and reliability, troubleshoot distributed systems, and participate in on-call support. Collaborate across engineering and product teams while using monitoring, testing, and documentation to maintain production quality.

Designs, builds, and operates secure, scalable cloud infrastructure and Kubernetes platforms for AI products and enterprise applications. Responsibilities include cloud architecture, networking, Terraform automation, container platforms, observability, security, disaster recovery, CI/CD enablement, developer self-service, and cost optimization. The role also supports AI infrastructure such as GPU workloads, RAG systems, vector databases, and LLM services while partnering with Engineering, AI, and Product teams.

Design, build, and scale high-throughput full-stack systems supporting climate intelligence products. Develop Node.js microservices, REST APIs, React applications, data models, aggregation pipelines, and Redis-based performance solutions. Architect and monitor AWS services, optimize production systems handling millions of API calls, and own features through deployment and support. Lead technical design discussions, review code, mentor engineers, and collaborate with product and data teams.

Leads hands-on software engineering across a cloud-native ESG and carbon intelligence platform. Responsibilities include coding, architecture, data modeling, AI and agentic feature development, DevOps, infrastructure, reliability, testing, code review, mentorship, delivery metrics, and stakeholder communication. The role requires ownership of scalable, auditable systems supporting ESG compliance, carbon calculations, MRV workflows, and agri-forestry credit generation.

Provides first-level support for Linux servers and cloud infrastructure. Performs basic administration, virtual machine operations, monitoring, troubleshooting, networking checks, log review, backups verification, access management, and documentation. Escalates complex issues and supports application and infrastructure teams with deployments and environment-related problems. The role is intended for entry-level candidates with foundational Linux, networking, cloud, and scripting knowledge, including freshers with lab or personal project experience.

Leads the enterprise QA strategy for AI-powered products, including LLM evaluations, agent workflows, APIs, microservices, cloud services, automation, performance testing, release sign-off, and reliability monitoring. Manages and mentors QA teams, builds automated testing frameworks and CI/CD integrations, validates model quality and safety, drives root-cause analysis, and communicates quality risks and release readiness to leadership.

Build and operate an AI-first developer platform, including CI/CD pipelines, Kubernetes-based tooling, developer products, and autonomous agents for remediation, upgrades, scanner triage, and credential rotation. Establish secure agent controls, observability, infrastructure as code, and zero-downtime practices. Run measurable experiments, improve DORA performance, collaborate with delivery teams, and influence the platform roadmap in a regulated environment.

Design, build, and operate scalable backend services and APIs for a cloud-native medical imaging platform. Own distributed systems throughout their lifecycle, including data pipelines, databases, testing, deployment, observability, incident response, security, and compliance. Collaborate with product, frontend, ML, and DevOps teams; contribute to architecture decisions, design reviews, technical standards, and mentoring. The role involves cross-time-zone collaboration across India and the US.