Enterprise Architect – AI Architect
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Key skills for this role
About the Role
DICETEK LLC is seeking an experienced Enterprise Architect with deep AI/ML expertise for a contract role. Requires 15+ years in architecture roles, hands-on AI/ML engineering, cloud platforms, and experience in regulated banking environments.
Key Skills for This Role
Responsibilities
- Define future state architectures and drive strategic platform decisions
- Design architectures grounded in real world delivery, operational, and production experience
- Influence architectural outcomes across multiple delivery teams
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or related field (or equivalent experience)
- 15+ years of experience in Enterprise Architecture, Domain Architecture, or Solution Architecture within complex, large scale environments
- Hands on engineering experience progressing from system administration, software engineering, platform engineering, or DevOps into architecture
- Proven experience defining future state architectures and driving strategic platform decisions
- Hands on expertise in AI/ML engineering and GenAI, MLOps, AIOps, AI Model life cycle management, Agentic System Design
- Experience in Data architecture
- Experience in Public Cloud platform with Hybrid integration (AWS, Azure) across AI, GenAI services
- Familiarity with security protocols and data protection standards in banking environments (e.g., OAuth2, TLS, PKI, DLP)
- Demonstrated experience operating within regulated, banking grade environments
- Proven ability to influence architectural outcomes across multiple delivery teams
- Excellent analytical, communication, and stakeholder management skills
Full Job Posting
Required Qualifications and Skills
- Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience)
- 15+ years of experience in Enterprise Architecture, Domain Architecture, or Solution Architecture roles within complex, large‑scale environments
- Strong and proven technical foundation built through hands‑on engineering experience, typically progressing from roles such as system administration, software engineering, platform engineering, or DevOps into architecture roles
- Proven experience defining future‑state architectures and driving strategic platform decisions, including technology evaluation and target‑state
- Proven hands on expertise in AI/ML engineering and GenAI, MLOps, AIOps, AI Model life cycle management, Agentic System Design
- Proven experience in Data architecture
- Proven experience in Public Cloud platform with Hybrid integration (AWS, Azure), across the AI, GenAI services
- Familiarity with security protocols and data protection standards in banking environments (e.g., OAuth2, TLS, PKI, DLP)
- Demonstrated ability to design architectures grounded in real‑world delivery, operational, and production experience — not purely theoretical models
- Demonstrated experience operating within regulated, banking‑grade environments
- Proven ability to influence architectural outcomes across multiple delivery teams without direct delivery ownership
- Strong working knowledge of relevant domain platforms and technologies (e.g., cloud platforms, containers, databases, middleware, security tooling, platform services)
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