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AI Architect
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Robert Half
Coppell, TX (In Person)
Full-Time
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Job Description
We are looking for an experienced AI Architect to shape and deliver enterprise AI capabilities that support global business operation. This position focuses on creating scalable architectures for generative AI, machine learning, intelligent automation, and advanced analytics while aligning technical strategy with business goals. The role will work closely with executives, IT leaders, and cross-functional teams to establish a practical AI roadmap and bring secure, production-ready solutions into day-to-day operations.
Responsibilities:
- Develop enterprise-wide AI architecture standards, reference models, and implementation guidelines to support consistent solution delivery across business functions.
- Design and deploy scalable platforms for generative AI, agent-based systems, machine learning, and analytics that can operate effectively in a global environment.
- Establish governance practices covering model oversight, responsible AI usage, security controls, compliance expectations, and lifecycle management.
- Partner with senior stakeholders to identify high-impact opportunities where AI can improve operational performance, decision-making, and business outcomes.
- Lead the architecture and rollout of AI-enabled assistants, knowledge tools, and automated workflows integrated with core enterprise applications and internal data sources.
- Create robust API, microservices, and orchestration patterns that enable reliable integration of AI services with business platforms and custom solutions.
- Build and refine retrieval-augmented generation solutions, vector-based search capabilities, prompt frameworks, and enterprise knowledge access models.
- Work with data engineering and platform teams to implement scalable AI pipelines, MLOps and LLMOps practices, monitoring, and cloud-based deployment patterns across major cloud environments.
- Evaluate emerging vendors, tools, and proof-of-concept solutions while guiding technical teams through architecture decisions, implementation challenges, and best practices.