AI Architect

AI Architect

We are seeking an experienced AI Architect to lead the design, development, and deployment of enterprise-grade AI solutions that drive transformation across our global consulting business. This role is pivotal in shaping the technical architecture for GenAI, ML, and agentic AI systems, ensuring scalability, security, and alignment with business objectives. The ideal candidate will possess deep expertise in AI systems, frameworks, and enterprise integration, coupled with a proven track record of delivering impactful AI solutions in complex organizational settings.

Why Join Us?

This is a high-visibility opportunity to shape how our company embeds AI across its global operations. You'll work at the intersection of architecture, innovation, and enterprise value creation, helping to define both near-term solutions and long-term strategy.

This position will offer flexibility for hybrid work schedules to include both in-office presence and telecommute/virtual work to be based in Dallas or Houston, TX.

Key Responsibilities:

• Define and maintain the overarching GenAI, LLMs, RAG pipelines, and autonomous agent systems
• Design and implement multiple agent orchestration workflows and agentic frameworks.
• Evaluate and select AI/Agentic tools, frameworks, and platforms (ex: LangChain, Semantic Kernel, Vertex AI, Azure OpenAI, AWS Bedrock, LangGraph, CrewAI)
• Align architectural decisions with business performance metrics, latency, security, cost, and explainability requirements.
• Assess emerging AI technologies and trends, recommending their adoption where appropriate
• Design scalable architectures that support composability, modularity, observability, and scalability of AI solutions, ensuring alignment with business strategy, data strategy, and technology roadmap
• Participate as a key stakeholder in the development of our AI Roadmap

Solution Design:

• Collaborate with cross-functional teams, including data architects, data scientists, enterprise architecture, security, AI product managers, and business stakeholders
• Guide proof-of-concept development and prototype evaluations to validate architecture decisions
• Provide architecture review, feedback, and mentorship to AI engineering teams
• Conduct structured build-vs-buy evaluations and contribute to platform roadmap decisions

Governance:

• Embed responsible AI principles, privacy, and governance frameworks into system design
• Ensure AI architecture complies with enterprise standards, security policies, and regulatory frameworks
• Partner with AI governance, data governance, security, and compliance teams to implement transparency and auditability