Top AWS Jobs in Pune

Design, develop, and deploy machine learning and computer vision models (classification, detection, segmentation, OCR, video analytics). Preprocess and annotate image/video datasets, optimize models for performance and scalability, integrate solutions into production, and document architectures and workflows.

As a Software Engineer, you'll develop high-quality software solutions, collaborate with teams, ensure secure coding, and implement unit testing.

Design, develop, and deploy production ML and generative AI solutions including RAG pipelines and LLM fine-tuning. Build scalable Python-based ML pipelines, implement model evaluation and monitoring, run experiments/A-B tests, collaborate with engineering and product, and contribute to AI system architecture.

The role involves frontend software development, collaborating on technical solutions, ensuring code quality, and maintaining systems. Requires expertise in JavaScript and frameworks like React.

Develop and maintain scalable web applications using Python and React.js, optimize APIs, manage applications on AWS and GCP, and ensure code quality through best practices.

Technical pre-sales architect for enterprise AI engagements. Design end-to-end AI/ML infrastructures (GPU clusters, networking, storage, MLOps, inference), whiteboard architectures, validate NVIDIA integrations, collaborate with cloud and partner teams, drive proofs-of-concept via ATC, and ensure clean handoff to delivery while supporting revenue-generating sales efforts.

Lead development and implementation of Dynamics 365 Business Central/MS NAV solutions. Design and build custom AL extensions, integrations (APIs, REST, OData, JSON, XML), configure BC for finance requirements, leverage AI for finance automation and forecasting, maintain cloud deployments (Azure/AWS), troubleshoot and optimize systems, and mentor team members.

As an Engineering Manager, you'll lead a Geo team, mentoring engineers while overseeing API development, backend coding, and nurturing agile practices.

Design, implement, and lead large-scale generative AI and ML systems (LLM fine-tuning, RAG, agents, Graph ML). Build REST APIs, deploy with Docker/Kubernetes, optimize big-data workflows, mentor engineers, and operate ML services on cloud platforms.

Lead design and delivery of cloud-native, event-driven platforms and applications. Drive full lifecycle development, champion engineering best practices, implement production-ready solutions, and build AI/LLM capabilities like RAG, embeddings, and model CI/CD across multi-cloud environments.

Design and implement an enterprise-scale cloud delivery platform. Build infrastructure automation with Terraform, Kubernetes, and Helm; migrate CI/CD to GitHub Actions; collaborate with architects, Security, and Operations to ensure secure, multi-tenant deployments; maintain code quality and developer experience; leverage AI assistants to accelerate delivery.

Build and maintain cloud delivery platforms using Terraform, Kubernetes, Helm and cloud-native tools. Develop CI/CD pipelines with GitHub Actions, migrate Jenkins/Azure DevOps pipelines, integrate observability and security tools (DataDog, SonarQube, Snyk), and improve developer experience through automation, documentation, and collaboration with global teams.

Build and maintain enterprise cloud delivery platforms using IaC, Kubernetes, and CI/CD. Develop automation, migrate pipelines to GitHub Actions, integrate observability and security tools, support platform scalability, and collaborate with global teams to improve developer experience and operational reliability.

Design and build a greenfield, multi-layer data warehouse and semantic metrics layer; separate analytics from OLTP; ensure data quality, traceability, tenant isolation, and high SLAs; enable linking of structured records to drone imagery/video; deliver self-service data access, observability, and infrastructure automation to scale across products and tenants.

Operate and improve AWS-hosted SaaS environments using DevOps, automation, and AI tools. Troubleshoot production issues, automate operational tasks, support on-call, administer Windows-based web hosting (.NET/IIS/SQL Server), build CI/CD and IaC (Terraform), enhance observability, and drive responsible AI-assisted engineering to reduce toil and increase reliability.

Design, automate, deploy, and maintain infrastructure services with a focus on Splunk, Terraform, and AWS. Drive automation, security/compliance, availability improvements, documentation, cross-team collaboration, and support multiple concurrent engineering projects.

Lead design and implementation of AI-powered QA and automation frameworks, drive Agentic AI/LLM integrations for test generation and self-healing, define CI/CD quality gates, oversee automated/manual testing, monitor quality metrics, present reports to leadership, and mentor engineering teams to modernize testing strategies.

Maintain and improve reliability, availability, and scalability of container platforms. Automate operational processes, respond to incidents, optimize performance, collaborate with development teams, and contribute to platform tooling and best practices.

Develop, train, evaluate, and optimize ML solutions and data pipelines; translate business requirements into production-ready ML code; perform feature engineering, model selection, and evaluation; document work, participate in code reviews, and support testing and data issue resolution.

Lead design and development of scalable cloud data platforms and ETL/ELT pipelines across AWS/Azure/GCP. Build and optimize data warehouses/lakehouses, implement MDM and governance, support analytics/BI, mentor junior engineers, and contribute to presales PoCs and solution designs.

Lead design, development, and optimization of scalable cloud data platforms and pipelines across AWS/Azure/GCP. Build ETL/ELT processes, data models, and lakehouse/warehouse solutions; implement MDM and governance; support analytics/BI, pre-sales PoCs, mentor junior engineers, and ensure security and cost/performance tuning.

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

Design, build, and own microservice-based backend services using Java and Spring Boot. Build REST APIs, implement event-driven systems, integrate message brokers, design MySQL schemas, optimize performance, collaborate across teams, and maintain scalable, highly available backend services.

The AI Engineer will develop, implement, and maintain AI systems and algorithms, ensuring data quality and deploying models in production. They will collaborate with teams to build data pipelines and ensure AI solutions meet requirements.

Lead design, training, and fine-tuning of large-scale ML/DL models (LLMs and generative systems) for drug discovery. Build scalable training pipelines, data pipelines, and production-ready model deployments; collaborate with engineering teams; translate research into applied AI solutions and continuously improve model performance and reproducibility.