Principal AI Architect
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Job Location:
Fort Worth, TX - USA
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
How will this role impact First Command
The Principal AI Architect will lead the design and implementation of enterprise AI architecture technical frameworks and governance standards to ensure responsible scalable and strategically aligned adoption of AI technologies. This role focuses on embedding AI best practices into First Commands enterprise architecture collaborating closely with data technology and governance teams.
What will the employee do in this role
- Strategic Leadership
- Contribute to enterprise AI strategy by defining architecture principles technical standards and governance models.
- Advise senior architects and technology leaders on scalable AI design patterns and integration approaches.
- AI Architecture and Infrastructure
- Define and evolve the enterprise AI architecture blueprint in alignment with First Commands business strategy cloud infrastructure and enterprise architecture frameworks (e.g. TOGAF BIZBOK).
- Standardize AI platforms tools and development practices to support reusability security observability and performance at scale.
- Collaborate with Enterprise Architecture Cloud Engineering and IT Operations to integrate LLM endpoints AI services and model pipelines into cloud-native environments (e.g. Azure OpenAI Azure AI Foundry).
- Establish enterprise-wide AI infrastructure patterns MLOps standards and orchestration practices that enable lifecycle management and compliance with internal controls.
- Proof-of-Concept (PoC) Management
- Support the design and technical evaluation of AI PoCs to validate feasibility and architectural fit.
- Recommend reusable components and scalable patterns based on PoC outcomes.
- Drive end-to-end PoC deliverydefining objectives coordinating cross-functional teams and ensuring validation metrics are aligned with enterprise KPIs.
- Maintain a transparent PoC governance framework that ensures stakeholder visibility controls experimentation risk and supports enterprise adoption decisions.
- Cross-Functional Collaboration
- Collaborate with product engineering and data teams to embed AI into platforms using approved architecture patterns.
- Partner with governance and compliance teams to ensure AI solutions meet internal standards and regulatory requirements.
- Governance and Risk Management
- Establish and maintain AI governance frameworks aligned with enterprise architecture and Responsible AI principles.
- Define technical policies for model lifecycle management performance monitoring and auditability.
- Collaborate with Risk Legal Compliance and Security teams to evaluate AI-related risks including data privacy bias mitigation and third-party model usage.
- Culture and Enablement
- Promote AI best practices and technical literacy across architecture and engineering teams.
- Contribute to internal knowledge hubs and communities of practice focused on scalable AI design.
- External Engagement
- Stay current with industry standards and emerging technologies to inform architectural decisions.
- Engage with external forums and vendors to benchmark practices and explore new tools.
- Supervisory Responsibility
- Provide technical mentorship to AI engineers and data scientists.
- Influence architectural decisions and promote adherence to governance standards.
What Skills & Qualifications do you need
- Masters degree in data science machine learning AI or a related field.
- 5-7 years of experience in AI/ML architecture infrastructure or engineering roles.
- Proven success designing and implementing enterprise-grade AI solutions aligned with business strategy.
- Deep understanding of AI/ML technologies including Generative AI LLM lifecycle management and Responsible AI frameworks and their integration into enterprise architecture.
- Hands-on familiarity with modern AI orchestration tools (e.g. LangChain RAG pipelines agent frameworks knowledge graphs).
- Strong ability to influence architectural decisions and drive governance across the AI delivery lifecycle.
Preferred
- Experience in financial services or other regulated industries.
- Familiarity with architecture and capability frameworks (e.g. TOGAF BIZBOK LeanIX).
- Experience with cloud-native AI platforms such as Azure OpenAI Azure AI Foundry Microsoft Copilot or similar.
#LI-NC1 #LI-hybrid
Required Experience:
Staff IC
Key Skills
- Kubernetes
- S3
- Google Cloud Platform
- Cassandra
- System Architecture
- Redshift
- AWS
- Cloud Architecture
- NoSQL
- UML
- Kafka
- Distributed Systems
About Company
With over 60 years of financial coaching experience and over 175 offices around the world, First Command's Financial Advisors are proud to serve America's military.
