DISCO
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EnterpriseAIPlatformEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Enterprise AI Platform Engineer at DISCO. Skills: Enterprise AI Platform, Production Engineering, Cloud Infrastructure, DevOps. Re-architect AI prototypes. Design cloud infrastructure”
Industry & Context.
Troubleshooting
Work authorization US
What They're Looking For.
Must Have
5-8 years software engineering experience, Production systems experience, Full-stack development experience, RESTful API design experience, Python proficiency, JavaScript/TypeScript proficiency, Cloud engineering expertise, Infrastructure-as-Code expertise, CI/CD tools expertise, Container technologies proficiency, Relational/NoSQL databases proficiency, API design proficiency, Integration patterns proficiency
Nice to Have
AI/ML platforms expertise, LangChain expertise, LlamaIndex expertise, RAG expertise, Workato expertise, Zapier expertise, Cloud Security operational experience, Observability tools operational experience, AWS IAM operational experience, Secrets Manager operational experience, DataDog operational experience, Grafana operational experience, Serverless architecture familiarity, Lambda familiarity, Frontend frameworks familiarity, React familiarity, Vue familiarity
What You'll Do.
Re-architect AI prototypes
Design cloud infrastructure
Implement CI/CD pipelines
Containerize applications
Develop integration APIs
Ensure secure deployment
Implement secrets management
Protect data encryption
Establish audit logging
Partner on security reviews
Design production-ready architectures
Design scalable architectures
Collaborate on technology selection
Collaborate on integration patterns
Establish engineering standards
Establish best practices
Create technical documentation
Support non-engineering teams
Mentor non-engineering teams
Code review prototypes
Troubleshoot prototype solutions
Build internal developer platforms
Build reusable IaC templates
Create technical documentation for stakeholders
How You'll Work.
Team & Collaboration
Cross-functional teams; AI Innovation Lab; Production engineering
Full Job Description
Your Impact 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. What You'll Do 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. Who You Are 5-8 years of software engineering experience focusing on production systems, full-stac
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