Cloud Solutions Architect Database Engineer AI Platform Architect

Overview

Design and build scalable cloud database security API and AI infrastructure for enterprise applications. Translate business requirements into secure production-ready technical solutions. Architect AI systems enabling complex business processes through LLMs.

What You'll Do25

• 1Architect and implement scalable secure high availability cloud environments for enterprise applications
• 2Design backend architecture supporting web applications internal systems integrations and AI powered solutions
• 3Develop production database environments including schemas tables relationships stored procedures views indexing strategies and data access patterns
• 4Optimize SQL Server databases for performance scalability reliability data integrity and security
• 5Establish database standards covering data modeling normalization indexing query optimization auditing backup recovery and disaster recovery
• 6Design secure RESTful APIs and backend services using C# ASP.NET Core and .NET technologies
• 7Define API contracts request response models validation standards error handling versioning documentation and integration patterns
• 8Implement authentication authorization solutions using OAuth 2.0 OpenID Connect JWT SSO RBAC and enterprise identity providers
• 9Design and enforce application API security standards including SSL TLS encryption secrets management certificate management secure configuration and least privilege access
• 10Implement secure communication between cloud services databases APIs external systems AI services and front end applications
• 11Create integration architectures for internal systems third party applications vendor APIs and enterprise platforms
• 12Design data pipelines ETL processes transformation services and system to system integrations where required
• 13Establish logging monitoring auditing alerting and observability standards across backend services and cloud infrastructure
• 14Develop scalable architectures supporting increasing users transaction volumes data volumes integrations AI workloads and application workloads
• 15Implement caching asynchronous processing queues background services and distributed architecture patterns when appropriate
• 16Develop and maintain CI CD pipelines and infrastructure deployment processes
• 17Collaborate with front end developers to define API requirements data contracts authentication flows AI service interactions and integration standards
• 18Design AI workflow architectures enabling large language models to perform complex business functions through process sequences system instructions prompt strategies retrieval mechanisms examples evaluation methods tool interactions and orchestration workflows
• 19Architect retrieval augmented generation RAG architectures retrieving enterprise information from databases documents APIs and vector stores
• 20Design secure AI integration patterns controlling LLM access to enterprise databases APIs internal systems and sensitive business information
• 21Establish AI evaluation testing monitoring and quality standards measuring accuracy reliability consistency security and effectiveness of AI powered workflows
• 22Translate business stakeholder requirements into technical and AI architectures
• 23Evaluate technical risks scalability requirements security concerns infrastructure costs AI usage costs and architectural tradeoffs
• 24Conduct architecture code reviews establishing backend database API cloud security and AI development standards
• 25Provide technical leadership mentoring developers on architecture code review and best practices

Salary Insight