Top AWS Jobs in Pune

Own the health and growth of Rubiscape’s SI, VAR, and cloud partner portfolio. Responsibilities include recruiting and enabling partners, driving co-sell pipeline and revenue, conducting joint business planning, coordinating deal registration and pricing, supporting competitive deals, tracking CRM metrics and MDF usage, and representing the company at ecosystem events. The role requires enterprise channel sales experience, knowledge of partner mechanics, CXO-level engagement, and cross-functional collaboration.

Develop and deploy generative AI applications, integrate LLM APIs, perform text analysis using traditional machine learning and GenAI, and manage the machine learning lifecycle from problem definition through deployment and monitoring. Collaborate with cross-functional teams, translate business needs into technical solutions, evaluate new GenAI techniques, and document technical concepts.

Lead the architecture and development of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems for intelligent networking. Drive the full software lifecycle from design through production operations, establish technical direction, mentor engineers, and improve system reliability, security, observability, performance, and scalability.

Lead the architecture and development of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive the full software lifecycle, establish technical direction, mentor engineers, and ensure production systems are secure, observable, resilient, and highly performant.

Lead the technical vision, architecture, development, testing, deployment, and operations of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Build secure, resilient, observable services processing high-volume network data; guide technical strategy, improve engineering practices, and mentor engineers. Translate complex technical challenges into production-ready solutions across intelligent networking, cloud platforms, analytics, and automation.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drives technical vision, builds secure and observable production services, mentors engineers, leads technical discussions, and improves system reliability and performance. Requires extensive software engineering and distributed systems experience, proficiency in a general-purpose programming language, cloud expertise, and familiarity with AI, stream processing, network telemetry, or large-scale analytics.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems. Defines technical strategy, builds secure and observable production services, processes high-volume network data, and mentors engineers. The role requires hands-on software engineering leadership across the full lifecycle, including design, coding, testing, cloud deployment, operations, and technical reviews.

Lead the architecture, development, testing, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Define technical vision, build secure and observable high-performance services, process large-scale network data, and integrate intelligent networking capabilities. Mentor engineers, lead technical discussions and reviews, improve system reliability and performance, and translate complex technical challenges into production-ready solutions.

Lead the architecture and development of scalable, secure, observable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive technical vision, software delivery, system reliability, and operational excellence while mentoring engineers. Build production platforms processing high-volume network and operational data, integrating cloud infrastructure, machine learning, telemetry, and automation capabilities.

Lead the architecture, development, testing, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems. Define technical vision, build secure and observable production services, process high-volume network data, mentor engineers, and guide technical strategy across intelligent networking and cloud-native platforms.

Lead Software Engineer responsible for designing high-performance Java applications, mentoring developers, and implementing DevOps practices while optimizing software delivery pipelines.

The Threat Intelligence Data Engineer designs and operates automated data collection systems for cybersecurity, focusing on discovering and indexing data from various web sources, including dark web and decentralized networks.

Lead delivery of cloud data platform solutions: design and build pipelines on Snowflake/Databricks using SQL, PySpark and ETL tools, implement CI/CD, work client-facing to run workshops, mentor junior staff, and identify business value.

As a Staff Data Platform Engineer, you will lead the design and development of data infrastructure, manage CI/CD processes, and implement observability for data pipelines.

Build and maintain cloud-native deployment platform: backend microservices, CRDs/operators, GitOps pipelines, staging environments, multi-cloud and bare-metal automation, CI/CD integrations, monitoring and automated remediation for zero-downtime global rollouts.

The role involves engaging clients to design and implement cloud-based insurance solutions, ensuring alignment with business needs and employing innovative approaches.

Leads end-to-end performance testing across SaaS applications, APIs, microservices, ETL pipelines, databases, Kubernetes, and cloud-native platforms. Designs load, stress, endurance, and scalability tests; analyzes application, database, and infrastructure bottlenecks; monitors systems with observability tools; validates Kubernetes performance; integrates tests into CI/CD pipelines; produces stakeholder-facing reports; supports performance tuning; and mentors junior engineers.

Designs, deploys, automates, and manages Azure/AWS cloud infrastructure, Kubernetes workloads, and CI/CD pipelines. Responsibilities include Terraform and Helm-based infrastructure automation, Jenkins and GitHub release automation, cloud networking, monitoring and logging with Prometheus, Grafana, Azure Monitor, CloudWatch, and related tools, plus container security, vulnerability scanning, Linux administration, troubleshooting, and DevSecOps implementation. Collaborates across development, QA, security, and operations teams and supports production releases.

Design, implement, operate, and maintain multi-cloud platforms across GCP, AWS, and Azure. Provide 24/7 cloud operations, troubleshooting, monitoring, security, compliance, backup, high availability, disaster recovery, and outage analysis. Automate infrastructure and deployment processes using Terraform, GitHub, scripting, and CI/CD practices. Support incident management, service requests, documentation, cloud workload migrations, and continuous improvement within ITIL-based operations.

Design and implement complex web applications, improve engineering and quality standards, create CI/CD pipelines, support technical hiring, and coach junior and mid-level engineers. The role requires advanced Node.js development, TypeScript and React, database querying, testing, Docker-based deployment, AWS infrastructure configuration, and Kafka knowledge.

Build and maintain full-stack web applications using React or Angular and .NET, Node.js, Laravel, or similar frameworks. Integrate LLM-powered features and use AI coding tools and autonomous agents to accelerate development, testing, and prototyping. Contribute to cloud infrastructure, deployments, databases, APIs, microservices, performance optimization, and solution design. Collaborate with AI specialists, international stakeholders, and distributed teams in Agile environments while maintaining high-quality, maintainable code.

Design and build distributed systems for a high-performance CI/CD execution platform. Responsibilities include orchestrating Supabase Branch lifecycle operations, provisioning ephemeral sandboxed environments on AWS, scheduling concurrent builds, optimizing pipelines through caching and artifact reuse, handling retries and failures, instrumenting observability, and developing configuration and infrastructure integrations. The role requires strong Go and TypeScript skills, cloud infrastructure experience, and a production operations mindset.

Design and deliver scalable end-to-end data pipelines, analytics platforms, data models, and enterprise dashboards. Build and optimize ETL/ELT solutions using Python, PySpark, and SQL; work with cloud platforms and data warehouses; ensure data quality, governance, security, and performance. Lead technical teams, review designs, mentor developers, engage clients, conduct requirements workshops, and provide solution estimates and architecture approaches.

Design and engineer Snowflake solutions using Cortex AI capabilities such as RAG, semantic search, and multi-agent systems. Apply capital markets expertise while communicating with and managing clients. Nice-to-have experience includes PostgreSQL, Talend, Azure or AWS, Denodo, Iceberg tables, and migration from Oracle or DB2 to Snowflake.

Build and optimize Starburst-based data pipelines and federated queries, integrate databases, data lakes, and warehouses, and ensure performance, reliability, and governance. Collaborate with analytics, AI/ML, and business teams to deliver scalable data platforms and solutions.