Top AWS Jobs in Pune

The Software Development Engineer I will design and implement microservices, improve system performance, and mentor junior engineers. Responsibilities include coding, debugging, and developing features from design to deployment in a remote setting.

Design, develop, and execute test plans and automated tests (including API and performance). Identify and track defects, collaborate with cross-functional teams, maintain CI/CD test automation, and use AI tools to support test strategy and automation.

As an Infrastructure Engineer, you will build and optimize storage and offloading infrastructure for multimodal robotics data, focusing on data movement, AWS optimization, and reliability across global operations.

Design, develop, and maintain scalable backend services; implement secure APIs; optimize system performance and reliability; collaborate with cross-functional teams.

The Technical Program Manager will lead projects in a remote setup, focusing on program planning, agile facilitation, and delivery management across globally distributed teams, particularly in the fintech domain.

The Application Support Engineer will ensure application reliability and performance, provide technical support, monitor issues, manage upgrades, and collaborate with teams and vendors.

The Partner AI Deployment Engineer will guide AWS engagements, shape technical strategy, build AI architectures, and mentor partners to drive successful AI deployments.

Build and maintain data pipelines, warehouses, and lakes on AWS; design processing algorithms; collaborate with data scientists to deploy ML models; drive platform performance, stability, and controls while leading or advising teams.

Design, implement, and maintain scalable AWS infrastructure and CI/CD pipelines. Automate provisioning (Terraform/CloudFormation/Ansible), manage containers (Docker/EKS), ensure monitoring, security, cost optimization, and disaster recovery, and collaborate with development and QA for reliable deployments.

Design and oversee technical architecture, define system standards, collaborate with stakeholders, guide engineering teams on implementation, ensure scalability, reliability, and alignment with business goals.

Design and define technical architecture, guide development teams on implementation, ensure scalability, performance, security, and alignment with business requirements. Collaborate with stakeholders and provide technical leadership across projects.

Architect and implement an AI-ready data platform using Snowflake, Databricks, and cloud services. Build batch and real-time PySpark/Kafka pipelines, manage vector DBs and embedding pipelines, enable ML/LLM ops, enforce data governance, and mentor engineering teams to ensure secure, reliable AI outputs.

Lead design and delivery of Generative AI solutions using Amazon Bedrock and orchestration frameworks. Build CI/CD pipelines, manage full-stack AWS infrastructure, ensure observability and AI governance, collaborate with stakeholders, apply Agile practices, mentor engineers, and integrate new AI innovations into production systems.

Design, develop, and deploy AWS cloud-native and serverless applications. Build Lambda-based APIs, microservices, and CI/CD pipelines; integrate with AWS services and third-party tools; implement monitoring, logging, and alerting; troubleshoot production issues; collaborate with customers and teams to meet technical requirements and improve architecture.

Build and maintain ETL pipelines into Snowflake using AWS services (S3, Glue, Lambda). Use orchestration (Control-M), CI/CD (Jenkins), and GitHub for deployments. Perform data analysis and support reporting (Tableau) and Postgres integrations.

DevOps Engineer role requiring 6-9 years' experience. Must have Python, Docker, Kubernetes, and Terraform skills. CI/CD, AWS and general DevOps experience are desirable. Location indicated as CHN.

Own and maintain backend services using .NET and AWS Serverless (Lambda). Build Kafka producers with AVRO/schema registry integration, design DynamoDB schemas, implement REST API integrations, ensure observability, reliability, and performance, and create backfill tooling while collaborating with cross-functional teams.