Enterprise AI Platform Engineer

Who you are

• 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)
• Expertise in specialized AI/ML platforms (LangChain, LlamaIndex, RAG) and integration tools (Workato, Zapier)
• Operational experience with Cloud Security and Observability tools, including AWS IAM, Secrets Manager, and monitoring systems like DataDog and Grafana. Familiarity with Serverless architecture (Lambda) and modern Frontend frameworks (React, Vue)

What the job involves

• 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

Benefits

• Start-up culture
• Open PTO
• Growth opportunities
• Medical, dental, and vision, 401(k)