Principal AI & DevOps Engineer

Revvity, Inc.; Mumbai; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Revvity, Inc. in Mumbai seeks a Principal AI & DevOps Engineer to lead strategic discovery, architecture assessment, and enterprise AI/ML initiatives. You will drive architecture and deliver scalable AI-powered applications using Python backends and JavaScript/Flutter frontends.

Responsibilities include LLM context engineering, end-to-end CI/CD pipelines, data governance, observability, and mentoring engineers to transform business needs into production-grade solutions.

Qualifications

• Bachelor's or Master's in Computer Science or equivalent.
• 8–12 years of hands-on experience in full-stack development.
• Proven DevOps & automation with CI/CD tooling and Infrastructure as Code (IaC).

Responsibilities

• Conduct enterprise systems audit and architecture assessment.
• Lead cross-functional discovery sessions to surface friction and map AI/ML roadmap.
• Evaluate AI/ML tools and benchmark technologies with clear rationale.
• Architect and deliver production-quality full-stack AI apps (Python backend, JS/Flutter frontend).
• Design context engineering strategies for LLMs and enterprise data orchestration.
• Own end-to-end CI/CD pipelines for LLM apps and automated testing.

Skills

Full-stack development

Python

JavaScript/Flutter

CI/CD

IaC

LLM context engineering

Education

Bachelor's or Master's in Computer Science

Tools

AWS CloudWatch

Job description

Job Title Principal AI & DevOps Engineer

Location(s) Mumbai

About Us

Revvity is a developer and provider of end-to-end solutions designed to help scientists, researchers, and clinicians solve the world's greatest health challenges. We pair the enthusiasm of an industry disruptor with the experience of a longtime leader. Our team of 11,000+ colleagues from around the globe are vital to our success and the reason we're 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.

What You'll 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 you've 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

• Bachelor's or Master's degree in Computer Science or equivalent field
• 8-12 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.