Senior Staff Software Developer, ServiceNow

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry
• 12+ years of experience in software engineering, with a track record of delivering high-quality products with deep expertise in full-stack development and cloud-native architecture with a Bachelor's degree; or 8 years and a Master's degree; or a PhD with 5 years experience in Computer Science, Engineering, or related technical field; or equivalent experience
• Strong Python skills for backend services, API development, and data tooling (notebook parsing, workflow generation)
• Proven track record of rapid execution in greenfield environments with evolving requirements
• Hands-on experience building and scaling developer platforms or internal tools at enterprise scale
• Deep understanding of cloud development environments (Coder, GitHub Codespaces, Gitpod, or similar)
• Strong Kubernetes and containerization expertise for cloud-native application deployment
• Experience with data workflows and tooling: Jupyter, notebooks, orchestration systems (Airflow/Argo), data catalogs
• Full professional proficiency in English
• Proficiency in Python, Java, or similar object-oriented languages
• Experience with modern front-end frameworks such as Angular, React, or Vue
• Strong knowledge of data structures, algorithms, object-oriented design, design patterns, and performance optimization
• Familiarity with automated testing frameworks (e.g., JUnit, Selenium, TestNG) and integrating tests into CI/CD pipelines
• Understanding software quality principles including reliability, observability, and production readiness
• Ability to troubleshoot complex systems and optimize performance across the stack
• Experience with AI-powered tools or workflows, including validation of datasets, model predictions, and inference consistency
• Comfort with development tools such as IDEs, debuggers, profilers, source control, and Unix-based systems
• VS Code ecosystem: Extension API, webview development, command palette, language servers, debugger protocols
• Coder or similar platforms: Workspace provisioning, remote development environments, infrastructure customization
• Jupyter ecosystem: JupyterHub, Jupyter Server, Papermill, nbconvert, or similar notebook tooling
• Kubernetes & containerization: Pod management, custom resource definitions, Helm charts, image security
• Infrastructure as Code: Terraform, Kubernetes operators, GitOps workflows
• Git workflows: Branching strategies, code review automation, CI/CD integration
• Modern data stack: Familiarity with Trino, dbt, Iceberg, Argo Workflows, or similar technologies
• API design: RESTful services, authentication (OAuth/SAML), webhook integrations
• Proven track record building internal developer platforms or productivity tools from scratch
• Experience designing opinionated workflows that balance flexibility with guardrails
• Strong understanding of developer personas: data scientists, analysts, engineers
• Ability to iterate rapidly with early adopters and incorporate feedback without over-engineering
• Experience with workspace security: secrets management, network policies, image scanning
• Comfort operating at startup velocity within enterprise constraints
• Proven ability to work autonomously and drive technical decisions in ambiguous, greenfield environments
• Strong bias toward action: prototype quickly, gather feedback, iterate aggressively
• Strong technical writing and documentation skills for developer-facing content
• Excellent collaboration skills across engineering, DevOps, and data teams
• Ability to establish technical foundations for new products with long-term vision while delivering short-term results

Desirable

• We are building a cloud-native data development platform that bridges the gap between exploratory analysis and production-grade workflows. As our founding Staff Software Developer focused on Cloud Development Infrastructure, you will design, architect, and rapidly implement a platform built on VS Code, Coder, and Jupyter that seamlessly integrates with our existing data stack (Trino, dbt, Iceberg, Lightdash, Argo Workflows)
• You will establish opinionated, automated pathways from notebook experimentation to production pipelines, moving at startup speed within an enterprise environment. This role demands aggressive execution: working prototype in 3 months, production-ready platform in 6 months
• This is a unique opportunity to build from the ground up and define how data development happens at ServiceNow's scale
• Design and develop scalable, maintainable, and reusable software components with a strong emphasis on performance and reliability
• Collaborate with product managers to translate requirements into well-architected solutions, owning features from design through delivery
• Build intuitive and extensible user experiences using modern UI frameworks, ensuring flexibility for customer-specific needs
• Contribute to the design and implementation of new products and features while enhancing existing product capabilities
• Integrate automated testing into development workflows to ensure consistent quality across releases
• Participate in design and code reviews ensuring best practices in performance, maintainability, and testability
• Develop comprehensive test strategies covering functional, regression, integration and performance aspects
• Foster a culture of continuous learning and improvement by sharing best practices in engineering and quality
• Promote a culture of engineering craftsmanship, knowledge-sharing, and thoughtful quality practices across the team
• Design and architect the foundational cloud development platform for notebook-based data workflows
• Lead technical decision-making on workspace provisioning, developer experience, and productionization pathways
• Establish best practices for notebook-to-production workflows, including git integration, parameterization, validation, and automated deployment
• Drive innovation in data development platforms, leveraging AI/ML tools for enhanced developer productivity
• Move fast: deliver working MVP in 3 months, production system scale in 6 months
• Build and customize cloud workspace infrastructure using Coder (open source) on Kubernetes
• Develop VS Code extensions (TypeScript) for productionization workflows: notebook validation, parameterization, and Argo Workflow generation
• Implement opinionated notebook templates and validation rules for production-ready data pipelines
• Create seamless integrations between notebooks and ServiceNow's data stack: Trino queries, Iceberg table outputs, Lightdash previews, dbt transformations
• Build backend services (Python) for workflow orchestration, notebook parsing, and metadata management
• Deploy JupyterHub initially, then progressively replace components with custom platform features based on user feedback
• Design container images with embedded security policies, pre-configured data access to Trino/Iceberg tables, and optimized dependencies
• Implement git-native workflows with automated notebook versioning, code review integration, and CI/CD pipelines
• Build observability and monitoring for workspace health, user activity, and pipeline success rates
• Establish infrastructure foundation that scales from 5 early adopters to 30+ practitioners within first year
• Create "template-based" notebook workflows with opinionated structure: parameterization (Papermill-style), Iceberg table outputs, validation checkpoints
• Build CLI and UI tooling for one-click productionization: notebook → Argo Workflow with minimal manual intervention
• Establish developer guardrails: credential management, data access policies, resource quotas
• Collaborate closely with early adopter data scientists to rapidly iterate on workflows and validate usability
• Prioritize platform stability and clear productionization paths over feature breadth in first 6 months
• Leverage cutting-edge AI development tools (e.g.. Cursor, Windsurf, ChatGPT, GitHub Copilot) to accelerate development velocity
• Establish AI-augmented development practices and mentor future team members on effective AI tool utilization
• Drive innovation in AI-assisted code generation, testing, and platform optimization
• Work autonomously with guidance from Engineering and FinOps leadership
• Collaborate with DevOps team on Kubernetes infrastructure, CI/CD pipelines, and security policies
• Partner with FinOps Tools team members working on Trino, dbt, Lightdash, and Iceberg to ensure seamless integrations
• Contribute to open-source projects in the notebook and developer tooling ecosystem