Revvity, Inc.

Join Revvity as a Full-Stack AI Engineering Intern to prototype generative AI solutions that improve enterprise productivity and empower employees. You’ll work across departments on LLM integrations, prompt engineering, AI evaluation, and full-stack tools.

Join Revvity as an AI Applications DevOps Intern in Mumbai, supporting the deployment, monitoring, testing, and infrastructure automation of cloud-based AI and LLM applications. You’ll gain hands-on experience with AWS, containers, infrastructure-as-code, and enterprise AI innovation.

Lead the architecture, automation, and operation of scalable AI/ML infrastructure for the Signals Platform. This principal-level role bridges AI research and software engineering to reliably deploy and monitor models in production.

Build and enhance scalable Salesforce solutions for Revvity using Apex, Lightning Web Components, Flow, integrations, and cloud automation. This hands-on role spans development, testing, deployment, troubleshooting, and production support across Sales Cloud and Service Cloud.

Lead the architecture, development, deployment, and scaling of enterprise AI/ML solutions as a Principal AI & DevOps Engineer. This hands-on technical leadership role combines full-stack AI application delivery, LLM context engineering, data pipelines, automation, and observability.

Lead the design and delivery of high-impact, scalable software systems using AI-native development practices. This senior technical leadership role combines architecture, hands-on coding, engineering mentorship, and end-to-end solution delivery.

Revvity is seeking a Senior Software QA Automation Engineer to design, develop, and execute automated tests for scalable enterprise software using Playwright and TypeScript. The role combines UI automation, functional and performance testing, defect analysis, and close collaboration with scrum and manual testing teams.

Lead hands-on architecture and implementation of a distributed microscopy data platform spanning instruments, on-premise systems, user PCs, and AWS cloud environments. The role focuses on high-throughput scientific data pipelines, backend interfaces, storage, search, transfer, and technical leadership.