Principal AI & DevOps Engineer

About Us

Revvity is a developer and provider of end-to-end solutions designed to help scientists researchers and clinicians solve the worlds greatest health challenges. We pair the enthusiasm of an industry disruptor with the experience of a longtime leader. Our team of 11000 colleagues from around the globe are vital to our success and the reason were able to push boundaries in pursuit of better human health.

Find your future at Revvity

Are a seasoned technologist who thrives at the intersection of artificial intelligence and business transformation Do you have a proven track record of turning complex AI/ML concepts into scalable production-grade systems that move the needle for enterprise operations If so we want to hear from you.

We are looking for a Principal AI & DevOps Engineer to join our team a strategic builder and technical leader who brings deep expertise sharp instincts and a bias for action. You wont just execute; youll shape the direction of how we architect deploy and scale AI/ML solutions across the organization.

What Youll Own

First 30 Days Strategic Discovery & Architecture Assessment

Enterprise Systems Audit: Rapidly assess our existing technical landscape business architecture and active AI workstreams bringing your experience to quickly identify gaps redundancies and high-leverage opportunities others might miss.

Cross-Functional Stakeholder Engagement: Lead structured discovery sessions across business units to surface operational friction points and define a prioritized roadmap for AI/ML intervention drawing on your experience translating business pain into technical solutions.

Technology Evaluation & Benchmarking: Apply your deep knowledge of emerging AI/ML technologies industry trends and software engineering best practices to evaluate our current toolchain and recommend improvements with clear rationale.

Strategic Value Mapping: Deliver a well-reasoned assessment of where generative AI can reduce manual overhead unlock creative capacity or create competitive advantage backed by your own experience doing exactly that.

Beyond 30 Days Build Lead and Scale

Full-Stack AI Application Development: Architect and deliver production-quality full-stack AI-powered applications leveraging Python backends and JavaScript/Flutter frontends with a focus on performance maintainability and user experience informed by years of hands-on delivery.

Context Engineering & LLM Optimization: Design and implement sophisticated context engineering strategies orchestrating enterprise data memory systems tool outputs and prompt chaining within LLM context windows to produce accurate structured and reliable outputs at scale.

End-to-End Pipeline Ownership: Own the full deployment lifecycle. Design implement and continuously improve CI/CD pipelines for LLM applications including automated testing frameworks applying best practices youve refined over your career.

Data Engineering & ML Lifecycle Management: Drive data quality pipeline integrity and dataset governance to fuel deployed ML models bringing mature engineering discipline to data validation query optimization and model input management.

Observability & Performance Engineering: Establish robust monitoring frameworks using tools like AWS CloudWatch define and track AI performance against business KPIs and deliver executive-ready dashboards and reports that connect system health to business outcomes.

Technical Leadership & Knowledge Sharing: Mentor peers through code reviews lead architectural discussions and present fully operational solutions during stakeholder demos translating complex AI/ML architecture into clear compelling narratives for both technical and non-technical audiences.

Required Qualifications

• Bachelors or Masters degree in Computer Science or equivalent field
• 812 years of hands-on experience in full-stack development
• Proven DevOps & Automation expertise: Deep experience with CI/CD tooling deployment workflows and Infrastructure as Code (IaC) in production environments

This role is designed for someone who brings their own perspective methodology and technical philosophy not just executes a playbook. We value engineers who have strong opinions loosely held and the experience to back them up.