Cloud Solutions Architect / Database Engineer / AI Platform Architect (NY, Manhattan)

Responsibilities

• Architect and implement scalable, secure, and highly available cloud environments for enterprise applications.
• Design the overall backend architecture supporting web applications, internal systems, integrations, and AI-powered solutions.
• Design, build, and maintain production database environments, including schemas, tables, relationships, stored procedures, views, indexing strategies, and data-access patterns.
• Develop and optimize SQL Server databases for performance, scalability, reliability, data integrity, and security.
• Establish database standards covering data modeling, normalization, indexing, query optimization, auditing, backup, recovery, and disaster recovery.
• Design and develop secure?RESTful APIs and backend services using C#, ASP.NET Core, and related .NET technologies.
• Build well-structured API and service layers that allow front-end developers to consume data and business functionality without requiring direct access to backend systems or databases.
• Define API contracts, request/response models, validation standards, error handling, versioning, documentation, and integration patterns.
• Implement authentication and authorization solutions using technologies and standards such as?OAuth 2.0, OpenID Connect, JWT, SSO, RBAC, and enterprise identity providers.
• Design and enforce application and API security standards, including SSL/TLS, encryption, secrets management, certificate management, secure configuration, and least-privilege access.
• Implement secure communication between cloud services, databases, APIs, external systems, AI services, and front-end applications.
• Design cloud networking and infrastructure components including application hosting, databases, storage, identity, networking, firewalls, gateways, load balancing, monitoring, logging, and availability strategies.
• Develop integration architectures for internal systems, third-party applications, vendor APIs, and enterprise platforms.
• Design data pipelines, ETL processes, data transformation services, and system-to-system integrations where required.
• Establish logging, monitoring, auditing, alerting, and observability standards across backend services and cloud infrastructure.