Enterprise Cloud, Database & AI Platform Architect

ABCO MAINTENANCE INC. (BIC# 1854)

St. Louis (MO)

On-site

USD 150,000 - 180,000

Full time

8 days ago

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Job summary

ABCO MAINTENANCE INC. is 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.

The ideal candidate will bring deep expertise in cloud architecture, C#/.NET, SQL Server, REST APIs, and AI platform architectures, with hands-on experience in OpenAI or Azure OpenAI, and a strong focus on secure, scalable production systems.

Qualifications

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.

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.