DevOps Engineer

Role : Devops Engineer

Experience level : 5 to 7 years

Location : Chennai

Who are we?

Crayon Data is a leading provider of AI-led revenue acceleration solutions, headquartered in Singapore with a presence in India and the UAE. Founded in 2012, our mission is to simplify the world’s choices.

Our flagship platform, maya.ai, helps enterprises in Banking, Fintech, and Travel unlock the value of their data to create hyperpersonalized experiences and drive sustainable revenue streams. maya.ai is powered by four “as a Service” components – Data, Recommendation, Customer Experience, and Marketplace – that work in unison to deliver tangible business outcomes.

Why Crayon? Why now?

Crayon is transforming into an AI-first company, and every Crayon (that’s what we call ourselves!) is on a journey of upskilling and expanding their capabilities in the AI and tech space.

We’re building an organization where automation, reliability, and scalability are foundational. If you're a DevOps engineer who thrives on building resilient infrastructure, streamlining CI / CD processes, and enabling teams to deploy faster and smarter—you’ll feel right at home here.

Our environment empowers engineers to experiment, optimize, and innovate with real-world challenges, cloud-native architectures, and cutting-edge tools. You won’t just be supporting systems—you’ll be shaping the infrastructure that powers Crayon’s AI future

Job Overview

The DevOps Engineer will be responsible for building and maintaining robust, scalable, and secure infrastructure to support development and operational needs. This role requires strong expertise in Linux systems, scripting, automation, and CI / CD pipeline management. The engineer will collaborate closely with development and IT teams to ensure smooth deployments, system reliability, and minimal downtime. Experience with monitoring tools, containerization (e.g., Docker, Kubernetes), and cloud platforms like AWS or Azure will be an added advantage.

What You’ll Do

• Build and manage scalable infrastructure to support deployment of machine learning and analytics models for key banking use cases such as cross-sell, upsell, churn prediction, and customer segmentation.
• Handle large-scale structured and unstructured data pipelines, ensuring availability, reliability, and performance.
• Translate business and technical requirements into robust DevOps solutions that enable data science and engineering teams to deploy efficiently.
• Collaborate closely with product, engineering, data science, and consulting teams to ensure seamless integration and delivery of production-ready systems.
• Continuously monitor, optimize, and automate infrastructure and deployment pipelines for performance and cost efficiency.
• Mentor junior engineers and contribute to best practices, documentation, and internal tool development.

Can you say “Yes, I have!” to the following?

Technical Expertise :

Can you say “Yes, I will!” to the following?

Brownie points for :

Come play, build, and grow with us.

Let’s co-create the future of AI at Crayon.