Top AWS Jobs in Pune

Build and maintain end-to-end applications using Python and React, including backend APIs, data layers, responsive user interfaces, integrations, background jobs, and microservices. Design secure, scalable software, implement unit testing and CI/CD pipelines, deploy to AWS or Azure, support production reliability, participate in code reviews, collaborate cross-functionally, and contribute to technical excellence, risk management, and governance.

Owns and optimizes shared demo environments for contact center and customer experience solutions. Designs reusable demonstrations and integrations using Zendesk, Amazon Connect, and AWS; supports custom presales demos and proof-of-concepts; manages releases, governance, security, reliability, cost, and automation; and creates technical documentation. Collaborates with internal teams, customers, vendors, and partners while independently prioritizing work and incorporating AI, analytics, and emerging platform capabilities.

Leads technical onboarding, enablement, and co-selling support for contact center partners. Designs scalable Zendesk, Amazon Connect, and AWS architectures; provides technical strategy, mentorship, solution guidance, demonstrations, proofs of concept, and implementation support. Develops partner training materials, ensures security and governance compliance, and promotes AI, machine learning, automation, and omnichannel contact center innovations. Collaborates with sales, engineering, vendors, and internal teams to drive partner success and accelerate solution deployment.

Own the reliability, scalability, security, and performance of large-scale Linux infrastructure supporting backup and disaster recovery services. Manage Kubernetes, infrastructure as code, CI/CD pipelines, monitoring, observability, incident response, and production troubleshooting. Automate operational tasks with Shell, Python, or Go; implement security controls; and collaborate with engineering and SRE teams to improve deployment processes and platform reliability.

Design, build, and operate AWS/Azure cloud infrastructure and DevOps workflows. Own IaC, CI/CD, container and serverless deployments, monitoring, security, cost optimization, and cloud migrations while automating operations and collaborating with development, data, and ML teams.

Lead design, development, and operation of a scalable search platform and data-intensive microservices. Drive reliability, SLAs, monitoring, incident response, code reviews, and mentor engineers while partnering with architects and PMs to deliver search experiences.

Build and maintain reliable, scalable, and secure infrastructure platforms, cloud environments, and deployment pipelines. Responsibilities include managing Kubernetes and OpenShift platforms, developing CI/CD automation, providing L3 production support, monitoring system performance, resolving incidents, implementing security controls, and collaborating with product managers, architects, and engineers. The role also involves scripting, infrastructure automation, risk management, and continuous improvement.

Provide Level 2 platform and application support for the Puma platform on AWS. Monitor infrastructure and applications (Zabbix, ELK), investigate incidents across Linux/Windows, Java/Tomcat, ActiveMQ, NGINX, and databases (Oracle, SQL Server). Perform post‑maintenance validation, RCA, escalation to L3, develop operational automation (Shell/Python), maintain runbooks in Confluence, and participate in shift/on‑call rotations.

Develop and maintain scalable applications across backend and UI layers. Responsibilities include coding, unit testing, deployment, documentation, performance troubleshooting, issue resolution, architecture discussions, system integration, and sprint delivery. The role uses modern practices including microservices, serverless computing, CI/CD, infrastructure as code, cloud platforms, and agile development. Engineers contribute to project planning, testing strategies, technical roadmaps, and operational excellence.

Design, develop, operate, and optimize large-scale software-defined networking solutions for NVIDIA AI Cloud environments. Responsibilities include building OVS/OVN control and data plane software, Kubernetes networking services, observability systems, CI/CD pipelines, GitOps integrations, and secure gRPC/REST services. The role owns production reliability, incident response, performance tuning, and upstream open-source contributions while collaborating with SRE, DevOps, and network engineering teams.

Leads the architecture, governance, integration, and delivery of AI-driven solutions across enterprise CRM, ERP, and iPaaS platforms. Designs AI/ML-enabled backend workflows, APIs, event-driven systems, automation pipelines, and production environments. Partners with technical and business stakeholders, ensures scalability, security, and compliance, and communicates architecture decisions. The role requires extensive enterprise architecture and systems integration experience, production AI implementation expertise, and knowledge of platforms such as Salesforce, SAP, MuleSoft, and related technologies.

Designs, operates, and improves scalable cloud infrastructure across GCP and AWS. Builds Terraform-based infrastructure, GitHub Actions CI/CD pipelines, observability, automation, and AI-enabled monitoring and remediation. Manages MySQL and SQL Server databases, Cloudflare services, security controls, repository governance, and incident response. Supports reliability, performance, cost optimization, compliance, and cloud modernization while providing 24/7 on-call coverage and mentoring junior engineers.

Design, implement, and manage security controls across multi-cloud and on-prem infrastructure. Lead cloud security, network security, IAM, endpoint protection, vulnerability management, incident response, and M&A security integrations. Conduct assessments, maintain documentation, embed security into designs, and ensure compliance with NIST/ISO/CSA standards while recommending tools and remediation to strengthen the security posture.

Develop and maintain scalable full-stack web applications across backend, frontend, databases, APIs, and cloud platforms. Responsibilities include designing applications, building services and responsive interfaces, optimizing SQL and NoSQL databases, integrating third-party services, troubleshooting production issues, writing secure maintainable code, and participating in testing, code reviews, and deployment. The role requires analytical problem-solving, understanding business requirements, effective communication, and adaptability across technology stacks.

Architect and build production-grade generative AI and agentic AI applications, including LLM workflows, multi-agent systems, RAG pipelines, APIs, and ML/GenAI infrastructure. Develop and optimize models, manage deployment and monitoring, apply responsible AI practices, and collaborate directly with customers. The role also involves mentoring engineers and shaping AI platform strategy.

Architects and builds scalable generative and agentic AI products from prototype through production. Designs LLM workflows, prompts, multi-agent systems, RAG pipelines, and APIs using LangChain and LangGraph. Owns ML and GenAI pipelines, including training, deployment, monitoring, and lifecycle management. Works directly with customers and cross-functional teams, promotes responsible AI, mentors engineers, and shapes AI platform strategy.

Develop and maintain full-stack .NET applications using C#, C/C++, AngularJS, and WinForms. Responsibilities include implementing features, debugging defects, conducting manual and automated testing, maintaining Azure DevOps pipelines and test infrastructure, performing code reviews, resolving incidents, and addressing security and compliance issues. The role collaborates with cross-functional teams and may require occasional onsite travel for training or project stabilization.

Lead software quality engineering for capital markets and equity derivatives systems. Develop test strategies, automated scripts, API and UI testing frameworks, and CI/CD integration. Analyze requirements, define acceptance criteria, perform root cause analysis, support defect resolution, and promote code quality. Guide testing architecture, risk controls, process improvements, and technical direction while advising stakeholders and mentoring engineers. Validate complex pricing, trading, lifecycle, structured product, and market data workflows.

Designs, develops, and manages enterprise-scale data platforms and ETL/ELT pipelines using dbt, Snowflake, Airflow, SQL, Python, and GitLab CI/CD. Responsibilities include data modeling, warehouse optimization, workflow monitoring, data governance, quality, observability, and performance tuning. The role supports AI/ML initiatives through feature-ready datasets and pipeline integration, collaborates with technical and business stakeholders, mentors team members, and contributes to architecture and engineering best practices.

Designs and governs Salesforce integration architecture across ERP, middleware, third-party applications, and enterprise systems. Defines integration patterns, API management, authentication, security, monitoring, error handling, and performance standards. Produces architecture documentation, guides API governance, collaborates with enterprise architects, and troubleshoots production issues. Requires extensive enterprise integration and Salesforce experience, strong knowledge of Salesforce APIs, middleware, event-driven architecture, microservices, and authentication protocols.

Own the production lifecycle for traditional ML and generative AI systems, including deployment pipelines, model registries, monitoring, retraining, governance, and incident response. Build reliable AWS-based infrastructure for LLM and agentic applications, establish observability and cost controls, and create operational standards, runbooks, and documentation. Partner with U.S.-based Data Science, Data Engineering, and Product teams while independently managing production workloads during India operating hours.

Lead software architecture and development for Lectora Online, including designing, coding, testing, troubleshooting, performance optimization, documentation, and technical standards. Own major product components, guide modernization and AI-powered features, lead testing strategies and automation, collaborate cross-functionally, and mentor engineers. The role requires expert Java and web application development skills, architectural decision-making, and technical leadership.

Design, build, test, and deploy production-grade agentic AI systems using Python, LangGraph, LangChain, AWS Bedrock, and orchestration tools. Integrate AI agents with APIs and business systems, implement memory and retrieval, establish observability and safeguards, and develop reusable SDKs and templates. Collaborate directly with clients to define requirements, run experiments, and rapidly deliver reliable AI solutions using modern software engineering, cloud deployment, and CI/CD practices.

Designs and maintains CI/CD pipelines, cloud infrastructure, infrastructure-as-code, and containerized environments. Improves scalability, reliability, security, monitoring, and automation; troubleshoots infrastructure and application issues; responds to incidents through on-call rotation; and collaborates with development and operations teams to support reliable software delivery.

Designs and maintains a centralized AI platform and agentic framework supporting secure deployment, management, and integration of AI agents. Responsibilities include building scalable agentic solutions, developing unified APIs, integrating agents into applications, optimizing cloud-native workloads, ensuring security and compliance, conducting capacity planning, mentoring engineers, and shaping the platform roadmap.