Top AWS Jobs in Pune

Lead technical strategy for complex enterprise deals, engage senior security executives, design solution architectures and POCs, run discovery workshops and demos, address security and regulatory requirements, enable handoffs to implementation and Customer Success, influence product roadmap, and mentor solution engineers.

Lead design and delivery of scalable, secure full-stack solutions using Java Spring Boot, cloud-native architectures, containers, and Angular. Influence technical strategy, mentor teams, collaborate with stakeholders, and ensure risk controls, testing, and performance for securitization financing platforms.

Build full-stack product surfaces, backend services, APIs, databases, dashboards, internal tools, vendor workflows, and observability for reinforcement learning data and evaluation systems. Develop interfaces for browsing environments, inspecting trajectories, reviewing quality, debugging failures, and understanding model behavior. Partner with research, operations, vendors, and go-to-market teams to translate ambiguous requirements into reliable products. The role also involves production debugging and cloud infrastructure collaboration.

Design, build and maintain cloud data pipelines, data warehouses and lakes; implement processing and analysis algorithms; collaborate with data scientists to deploy ML models; lead or support team operations and ensure security, controls and continuous improvement.

Lead design, development, and delivery of scalable, secure data platform and engineering solutions. Drive Python/PySpark development, AWS cloud deployments, data warehousing, ETL, operational stability, and cross-functional collaboration while promoting code quality, testing, and technical leadership.

Coordinate Sales, Finance, and Legal approvals; resolve Salesforce queues and case-management issues; create private offers in AWS, Azure, and GCP marketplaces; audit SaaS contract documentation; and monitor the sales pipeline to remove bottlenecks and accelerate deal completion.

Lead distributed engineering teams to deliver scalable, high-volume user-facing web applications for IT Asset Disposition and reverse logistics. Partner with Business and Product to set priorities, manage delivery, incident management, production support, and reliability. Improve onshore/offshore collaboration, use Jira/Confluence for planning and documentation, and drive operational excellence and stakeholder communication in a fast-paced environment.

Own and improve production infrastructure reliability, deployments, Infrastructure-as-Code, Kubernetes environments, automation, CI/CD, monitoring, alerting, and observability. Investigate incidents, optimize system performance, maintain documentation and runbooks, and support DNS, WAF, CDN, and caching infrastructure. The role requires strong Linux administration, Bash scripting, networking, Git, and containerization skills, with independent ownership and collaboration across development and operations teams.

The Technical Marketing Engineer will create technical content, demonstrate products, engage with developers, collaborate cross-functionally, and support marketing initiatives.

The DevOps Engineer designs and manages AWS cloud infrastructure, automates operations, develops CI/CD pipelines, and ensures robust monitoring and observability.

Build end-to-end infrastructure for AI agents: design React/TypeScript UIs, implement Python agent harnesses, develop Kubeflow-based MLOps pipelines, fine-tune foundation LLMs (LoRA/QLoRA/SFT/RLHF), deploy and operate services on Kubernetes, integrate agent frameworks, and apply software engineering best practices, testing, and CI/CD.

Design and implement production-grade AI agent harnesses, build and operate MLOps pipelines with Kubeflow, fine-tune foundation LLMs (LoRA/QLoRA, SFT, RLHF), deploy and manage services on Kubernetes, integrate agent frameworks, and apply software engineering best practices to move models from prototype to production.

Own and improve reliability of deployment and release systems: define SLOs/SLA/error budgets, instrument pre-production, build monitoring and synthetic tests, run on-call and incident response, create runbooks and DR readiness, and automate deploys and observability to reduce MTTD/MTTR.

Design, develop, and deploy integration applications and microservices using MuleSoft. Build APIs, middleware integrations, and CI/CD pipelines; write clean code, unit tests, and database/security best practices; collaborate with Salesforce teams, QA, and BAs to deliver scalable integrations.

Perform exploratory analysis, build dashboards and reports (Tableau), write SQL queries, use Python for data cleaning and predictive models, collaborate with stakeholders, communicate insights, and maintain data models, pipelines, and quality checks.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

Design, build, and maintain scalable test automation frameworks and suites for web, API, microservices, and backend systems. Integrate tests into CI/CD, perform functional, integration, regression, performance and E2E testing, analyze results, report defects, and drive quality engineering best practices across teams.

As a Backend Engineer, you will develop and maintain core backend infrastructure, build integrations, and work closely with frontend engineers to enhance user experience.

As a Senior Backend Engineer, you will develop and maintain backend systems, collaborate with frontend teams, and leverage AI for finance solutions.

Provide customer-facing DevOps and platform engineering support: debug OpenTelemetry instrumentation, optimize ClickHouse, troubleshoot Kubernetes, design observability solutions, build tooling and automation, engage the open-source community, and establish scalable customer engineering processes.

The Staff Platform Engineer will lead the architecture, development, and scaling of API-based transaction processing systems, ensuring reliability and performance while mentoring other engineers.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

The Support & Implementation Engineer will implement solutions, troubleshoot customer issues, ensure technical documentation accuracy, and collaborate with engineering teams.

The Applied AI Researcher will design experiments, train models, and build pipelines for a GenAI platform while contributing to research and deploying systems in production.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.