Senior Software Engineer - Platform & MLOps

At Serko, we believe something incredible happens when people come face-to-face. That’s why we’re on a mission to engineer a frictionless, next-generation business travel marketplace. We don’t just manage travel; we are leveraging advanced AI and cutting-edge tech to eliminate the complexity of global movement.

When you join Serko, you join a global collective of passionate technologists who show up as their true selves to build world-class products. With established hubs across New Zealand, Australia, North America, India and China - your code and ideas will impact millions of corporate travelers worldwide.

If you're ready to challenge the status quo and build the future of travel tech, your next journey starts here.

In this role, you will champion the developer experience by building the internal platform and tooling that every AI engineer at our company trusts and relies on. You’ll craft intuitive dashboards, user-friendly CLI tools, clean APIs, and elegant automation.

We’re hiring a Senior Full Stack Engineer to own the end-to-end development of our next-gen AI products either based in Washington or California State.

Requirements

• Your work will ensure that deploying and operating AI models is a seamless, safe, and empowering self-service journey, allowing our entire engineering community to thrive and scale together.

What You’ll Do

• Craft Beautiful Internal UIs: Develop intuitive and accessible internal platform interfaces—such as dashboards, model registries, and experiment trackers—using React and Next.js to elevate our internal developer experience.
• Nurture Backend Infrastructure: Design and support reliable backend services and APIs in Python, ensuring our application teams can seamlessly tap into the platform's full capabilities.
• Build Safe, Sustainable Automation: Create and refine thoughtful automation for model deployment, rollbacks, and scaling workflows using scripts, APIs, and Infrastructure as Code (IaC), embedding safety and predictability into every release.
• Cultivate System Visibility: Weave monitoring and observability tools (such as Grafana, Prometheus, DataDog, and LangSmith) directly into the platform, giving our teams the clarity and insights they need to succeed.
• Champion Code Quality & Trust: Write comprehensive testing, evaluation, and validation logic for machine learning pipeline components to ensure high reliability and product excellence.
• Partner with Internal Teams: Act as a supportive resource for our internal engineering community, listening to their experiences and gathering empathetic feedback to continuously iterate on our tooling.
• Share Knowledge Generously: Foster a collaborative environment by documenting systems clearly and contributing to engineering wikis and runbooks so that the entire team can grow together.

What you'll bring

• We believe that exceptional engineering stems from continuous growth and diverse experiences. We are looking for a collaborative partner who has spent 5+ years honing their craft in full-stack engineering and wants to make a lasting impact on our developer community.

You will be a great fit if you bring:

• Core Backend Comfort: A deep comfort with Python, paired with hands-on experience building dependable backend services and clean REST APIs.
• An Eye for Internal Tooling: A genuine appreciation for crafting responsive dashboards and internal tools using TypeScript and React.
• Production AI Experience: Experience caring for and managing machine learning-based applications within a live production ecosystem.
• Cloud & DevOps Literacy: A foundational comfort navigating cloud platforms (AWS, GCP, or Azure), alongside a basic understanding of Docker and Kubernetes.
• A Collaborative Spirit: A history of working hand-in-hand with data or machine learning engineering teams, respecting and learning from different technical perspectives.
• Understanding of System Flow: A solid foundational understanding of databases, job queuing systems, and asynchronous workflows.
• Creative Problem-Solving: A natural curiosity and comfort when facing open-ended or ambiguous technical challenges, with the ability to turn abstract ideas into structured, clear steps forward.