Security Architect| Enterprise AI Governance Platform

Buchanan Technologies; Dallas (TX); On-site; USD 80,000 - 110,000; Part time

Job summary

Buchanan Technologies is looking for an experienced AI Architect for a short-term consulting engagement in Dallas, Texas. The focus of this role is to enhance an enterprise AI governance platform, emphasizing secure integrations and integration engineering.

The successful candidate will extend existing applications with TypeScript and Node.js, and ensure compliance with identity management standards. If you have a strong background in security engineering and cloud deployment, we want to hear from you.

Qualifications

• Strong development experience with TypeScript, Node.js, and React.
• Enterprise identity and access management experience (OIDC, OAuth2, SAML, SCIM).
• Strong security engineering background focusing on secrets management and encryption.

Responsibilities

• Design and implement secure, scalable integrations across the enterprise AI governance platform.
• Extend existing codebase and integrate with enterprise systems.
• Support policy enforcement capabilities and audit logging.

Skills

TypeScript

Node.js

React

Enterprise identity management

Audit logging integration

Security engineering

Docker

Kubernetes

Tools

OPA/Rego

Terraform

Job description

Security Architect| Enterprise AI Governance Platform Emerging Technologies & AI Dallas , Texas 10332 Jun 23, 2026

Job Description: AI Architect | Enterprise AI Governance Platform

Engagement Type: Short‑term consulting engagement

Initial Duration: 90 days, with potential extension

Role: AI Architect / Integration & Security Engineer

Focus Area: Enterprise AI governance, integration engineering, security architecture, and platform modernization

Role Overview: We are seeking an experienced AI Architect to support a short‑term consulting engagement focused on advancing an internal enterprise AI governance platform from a working prototype to a proof‑of‑concept operating against real enterprise data.

This role is primarily focused on integration, security engineering, enterprise identity, policy enforcement, auditability, and platform portability. The ideal candidate will have strong experience extending existing TypeScript/Node.js and React applications while integrating with enterprise systems in secure, governed environments.

This is not a model training, machine learning, or data science role. The work centers on replacing prototype or stubbed components with live, governed enterprise integrations while maintaining a vendor‑neutral and portable architecture suitable for deployment on managed infrastructure.

Key Responsibilities

The AI Architect will be responsible for helping design and implement secure, scalable, and portable integrations across the enterprise AI governance platform. Responsibilities include:

• Extend and enhance an existing TypeScript, Node.js, and React codebase.
• Replace stubbed or prototype components with live integrations to enterprise systems.
• Integrate with enterprise identity and access management systems using standards such as OIDC, OAuth2, SAML, SCIM, and token exchange/on‑behalf‑of flows.
• Design and implement least‑privilege access patterns for data‑source and connector integrations.
• Support policy‑as‑code and policy enforcement capabilities using tools such as OPA/Rego or equivalent frameworks.
• Implement secure, immutable, and non‑repudiable audit logging capabilities.
• Integrate platform audit events with enterprise SIEM or security monitoring tools.
• Support LLM/model routing and gateway integration across multiple providers while avoiding single‑vendor lock‑in.
• Design and implement secure handling of secrets, encryption, and key custody.
• Support containerized, cloud‑neutral deployment patterns using Docker, Kubernetes, and Helm.
• Help ensure the architecture remains portable, provider‑agnostic, and suitable for deployment into managed infrastructure.

Required Skills and Experience

• Strong development experience with TypeScript, Node.js, and React.
• Experience extending or modernizing an existing enterprise application codebase.
• Enterprise identity and access management experience, including:
  • OIDC
  • OAuth2
  • SAML
  • SCIM
  • Token exchange / on‑behalf‑of flows
• Data‑source and connector engineering experience.
• Strong understanding of least‑privilege access models.
• Policy‑as‑code or policy enforcement experience, preferably with OPA/Rego or similar tools.
• Audit logging and SIEM integration experience.
• Experience designing immutable, traceable, and non‑repudiable event handling.
• Experience integrating LLM/model gateways or model routing layers across multiple providers.
• Ability to design for provider abstraction and avoid single‑platform coupling.
• Strong security engineering background, including:
  • Secrets management
  • Encryption
  • Key custody
  • Secure service‑to‑service communication
• Containerization and deployment experience with:
  • Docker
  • Kubernetes
  • Helm
• Strong architectural judgment and ability to balance prototype acceleration with enterprise‑grade security and governance requirements.

Strongly Preferred Qualifications

• Experience working in regulated, government, or DoD‑adjacent environments.
• Familiarity with NIST 800‑53, RMF, or similar authorization and accreditation frameworks.
• Experience supporting security authorization, accreditation, or compliance documentation.
• API gateway and reverse‑proxy architecture experience.
• Network egress control and secure integration patterns.
• CI/CD pipeline development and deployment automation.
• Infrastructure‑as‑code experience, especially with Terraform.
• Experience building cloud‑neutral or hybrid‑cloud enterprise platforms.

Ideal Candidate Profile

The successful candidate is a hands‑on architect or senior engineer who can move comfortably between application development, integration architecture, security engineering, and enterprise deployment considerations.

We are especially interested in candidates who:

• Design for portability, abstraction, and long‑term maintainability.
• Have experience integrating enterprise platforms with secure identity, logging, data access, and policy systems.
• Understand how to build governed AI infrastructure without becoming dependent on a single model provider or cloud platform.
• Can operate effectively in a short‑term consulting engagement with a focused scope and rapid execution expectations.
• Are comfortable working with sensitive enterprise data and security‑conscious stakeholders.

Engagement Deliverables

• Live enterprise identity integration replacing prototype authentication flows.
• Secure data‑source connector implementation using least‑privilege access.
• Policy enforcement integration.
• Audit logging and SIEM event integration.
• LLM/model gateway or routing integration across multiple providers.
• Containerized deployment artifacts and configuration updates.
• Security and architecture recommendations supporting future managed infrastructure deployment.