Enterprise AI Platform Engineer, DISCO

• 5-8 years of software engineering experience focusing on production systems, full-stack development (Python/TypeScript), and RESTful API design
• Deep expertise in cloud infrastructure (AWS/Azure), containerization (Docker/Kubernetes) and building robust DevOps CI/CD pipelines
• Proven track record of transitioning MVPs to production environments or contributing to platform engineering and developer productivity
• Proficient in Python, JavaScript/TypeScript, and modern framework
• Strong Python skills and deep expertise in cloud engineering (AWS/Azure equivalents),
• Infrastructure-as-Code (Terraform/CloudFormation), and CI/CD tools (e.g., GitHub Actions, Jenkins)
• Proficiency in container technologies (Docker, Kubernetes/EKS), relational/NoSQL databases (PostgreSQL, Redis), and designing APIs and integration patterns (REST, OAuth, API gateways)

Desirable

• The Enterprise AI Platform Engineer transforms citizen-developed AI prototypes (using Python, Workato, and Claude Code) into secure, scalable, production-grade enterprise systems
• This role is a vital link between the AI Innovation Lab and production engineering, evolving experimental Minimum Viable Products (MVPs) into long-term corporate capabilities
• Production Engineering and Deployment: Re-architect initial AI prototypes (Python, Workato, Claude Code) for secure, scalable enterprise deployment
• This includes designing cloud infrastructure (AWS/Azure), implementing CI/CD pipelines, containerizing applications (Docker/Kubernetes), developing integration APIs, and setting up comprehensive monitoring and observability for all production AI systems
• Security and Compliance: Ensure secure deployment by design, implementing robust secrets management and protecting data through encryption at rest and in transit
• This role also establishes comprehensive audit logging, partners on critical security reviews, and validates ongoing compliance with enterprise policies and regulatory standards
• Solution Architecture and Design: The role involves reviewing prototypes to design production-ready and scalable architectures for 1,000+ users, while collaborating on technology selection and integration patterns
• Additionally, the engineer establishes engineering standards and best practices and creates comprehensive technical documentation
• Developer Enablement and Support: This role also involves supporting and mentoring non-engineering teams, including code review and troubleshooting for prototype solutions, alongside building internal developer platforms and reusable infrastructure-as-code templates to accelerate development
• A final key responsibility is training the team on DevOps practices and creating clear technical documentation for all stakeholders