What are the responsibilities and job description for the AI Architect position at Jobs via Dice?
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We are seeking a senior AI Architect (consultant) to lead enterprise AI adoption—not just build models, but design, govern, and operationalize AI across the organization. This role requires someone who can work with leadership, drive execution, and ensure secure, scalable implementation of AI and agent-based systems.
What This Person Will Do
We are seeking a senior AI Architect (consultant) to lead enterprise AI adoption—not just build models, but design, govern, and operationalize AI across the organization. This role requires someone who can work with leadership, drive execution, and ensure secure, scalable implementation of AI and agent-based systems.
What This Person Will Do
- Lead end-to-end AI architecture across Azure (OpenAI, ML, data, security)
- Define and implement AI/agent strategy (RAG, APIs, MCP, orchestration frameworks)
- Drive internal AI enablement (tools, workflows, training, best practices)
- Partner with executives and stakeholders to prioritize and execute AI initiatives
- Design and oversee LLM integration (model selection, performance tuning, cost optimization)
- Establish governance, security, and guardrails to prevent misuse or risk
- Build scalable systems for continuous improvement and integration of AI capabilities
- Guide teams on prompting, evaluation, and iterative optimization of outputs
- Proven experience as an AI Architect / Enterprise Architect (not just developer)
- Strong Azure ecosystem expertise (Azure OpenAI, data platforms, security, identity)
- Deep understanding of:
- RAG vs API-based vs agent-based architectures
- LLM capabilities, tradeoffs, and model selection
- System design for scalable AI deployment
- Experience implementing secure, production-grade AI systems
- Ability to lead cross-functional teams and influence leadership
- Experience building AI strategy execution roadmap, not just coding solutions
- Primarily a hands-on AI/ML developer with no architecture ownership
- No experience with enterprise-scale systems or security considerations
- Limited exposure to LLM architecture decisions (RAG, agents, orchestration)
- Has not worked directly with business stakeholders or leadership
- Enterprise consulting or architecture roles
- Experience rolling out AI capabilities across an organization
- Comfortable acting as both strategic advisor and execution driver