Cloud Solutions Architect / Database Engineer / AI Platform Architect

Bic# 1854 • Manhattan, NY

4d

About The Position

We are seeking a highly experienced Cloud Solutions Architect / Database Engineer / AI Platform Architect to design and build the cloud, database, security, API, and AI infrastructure that supports our enterprise applications. Compensation for this role will be between $150k-$180k depending on experience. This role will be responsible for establishing scalable cloud architecture, designing and engineering production databases, developing secure APIs and integration services, implementing authentication and application security standards, and architecting the AI foundation of our applications. The architect will build the backend and AI service layers that allow front-end developers to securely and efficiently consume application data, business functionality, and AI-powered capabilities. The ideal candidate will have deep expertise in cloud architecture, C#/.NET, SQL Server, database engineering, REST APIs, application security, authentication, Azure or AWS, enterprise integrations, and production AI architecture. This individual should be capable of taking business and application requirements and translating them into secure, scalable, production-ready technical solutions. Experience with AI and Large Language Model (LLM) platforms is required, particularly when designing the infrastructure, data access, security, APIs, and application architecture necessary to support AI-powered enterprise solutions. The ideal candidate will have hands-on experience building production AI applications using OpenAI, Azure OpenAI, Anthropic, Google AI, or comparable LLM technologies, including designing workflows that enable AI to execute complex business processes through structured instructions, examples, retrieval strategies, orchestration, and enterprise data integration. This role requires experience developing AI as an operational component of an application, not simply integrating an AI API or adding chatbot functionality.

Requirements

• 8+ years of professional software development, cloud engineering, database engineering, or software architecture experience.
• Demonstrated experience designing production cloud and backend architectures for enterprise applications.
• Strong expertise with C#, .NET, ASP.NET Core, and RESTful API development.
• Advanced SQL Server and database engineering experience.
• Strong experience with relational data modeling, database architecture, stored procedures, indexing, query optimization, execution plans, and performance tuning.
• Experience designing databases for high-volume, production enterprise applications.
• Strong experience designing secure API and service architectures consumed by modern web applications.
• Strong understanding of API contracts, versioning, validation, error handling, documentation, and service-layer architecture.
• Extensive experience with authentication and authorization technologies including OAuth 2.0, OpenID Connect, JWT, SSO, and role-based access control.
• Strong understanding of SSL/TLS, encryption, certificate management, secrets management, secure credential storage, and application security best practices.
• Production experience with Microsoft Azure, AWS, or comparable enterprise cloud environments.
• Experience designing cloud networking, compute, storage, database, identity, monitoring, and security infrastructure.
• Strong understanding of distributed systems, scalability, availability, fault tolerance, disaster recovery, and production support.
• Experience with Git, CI/CD methodologies, deployment pipelines, and automated application deployment.
• Demonstrated experience designing, building, and deploying AI-powered applications using OpenAI, Azure OpenAI, Anthropic, Google AI, or similar LLM platforms.
• Candidates should have experience creating AI workflows that enable models to perform business processes through structured prompts and system instructions, process sequencing, examples, retrieval, evaluation, tool use, orchestration, and production integration—not simply consuming AI APIs.
• Experience designing AI capabilities as integrated components of enterprise applications and business workflows.
• Ability to translate business processes into technical workflows, data requirements, API interactions, AI instructions, and system architectures.
• Strong troubleshooting, analytical, documentation, and communication skills.
• Experience providing technical leadership, architecture guidance, and mentoring to software development teams.

Nice To Haves

• Microsoft Azure architecture experience, including services such as Azure App Service, Azure SQL, Azure Functions, Azure Storage, Key Vault, Microsoft Entra ID, API Management, Application Insights, and Azure networking.
• Experience with AWS or multi-cloud architectures.
• Experience with Docker, Kubernetes, containerized applications, and container orchestration.
• Experience with API gateways, reverse proxies, load balancers, message queues, caching platforms, and event-driven architectures.
• Experience with Infrastructure as Code technologies such as Terraform, Bicep, ARM templates, or CloudFormation.
• Experience designing enterprise integration architectures and ETL/data-processing pipelines.
• Experience with data warehousing, reporting databases, and business intelligence architectures.
• Hands-on experience designing and building production AI applications using OpenAI, Azure OpenAI, Anthropic, Google AI, or comparable generative AI platforms.
• Experience architecting AI workflows, prompt engineering, system instructions, Retrieval-Augmented Generation (RAG), vector databases, embeddings, semantic search, AI agents, tool/function calling, orchestration frameworks, and evaluation methodologies for enterprise AI solutions.
• Experience designing AI systems that incorporate business workflows through structured process definitions, contextual examples, enterprise knowledge retrieval, tool use, and iterative refinement, enabling AI to reliably execute operational business tasks.
• Experience designing secure architectures that allow AI systems to interact with enterprise databases, APIs, internal systems, and business information while maintaining appropriate authorization and data-access controls.
• Familiarity with Angular, React, Blazor, or other modern front-end frameworks sufficient to effectively design APIs and services supporting front-end development.
• Experience with IIS and Windows Server environments.
• Experience with automated testing, performance testing, security testing, and vulnerability management.

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.
• Design scalable architectures capable of supporting increasing users, transaction volumes, data volumes, integrations, AI workloads, and application workloads.
• Implement caching, asynchronous processing, queues, background services, and other distributed architecture patterns when appropriate.
• Develop and maintain CI/CD pipelines and infrastructure deployment processes.
• Work closely with front-end developers to define API requirements, data contracts, authentication flows, AI service interactions, and integration standards.
• Design and implement AI workflow architectures that enable Large Language Models to perform complex business functions by defining process sequences, system instructions, prompt strategies, retrieval mechanisms, examples, evaluation methods, tool interactions, and orchestration workflows.
• Architect AI systems capable of incorporating enterprise knowledge and business processes through structured process definitions, contextual examples, retrieval, tool use, and iterative refinement so that AI can reliably execute operational business tasks.
• Design Retrieval-Augmented Generation (RAG) architectures that securely retrieve relevant enterprise information from databases, documents, APIs, vector stores, and other approved business data sources.
• Design secure AI integration patterns that control how LLMs access enterprise databases, APIs, internal systems, and sensitive business information.
• Establish AI evaluation, testing, monitoring, and quality standards to measure accuracy, reliability, consistency, security, and effectiveness of AI-powered workflows.
• Collaborate with business stakeholders and development teams to translate application requirements and business processes into technical and AI architectures.
• Evaluate technical risks, scalability requirements, security concerns, infrastructure costs, AI usage costs, and architectural tradeoffs.
• Conduct architecture and code reviews and establish backend, database, API, cloud, security, and AI development standards.
• Provide technical leadership and mentoring to developers working within the architecture.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed