Lead AI Architect

Title:

Lead AI Architect

Location:

Either Dallas, TX or Houston, TX (hybrid)
Duration:
Direct Hire
Compensation: $200K-$240K per year
Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S.

We are seeking an experienced Lead 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.

• 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: Lang Chain, Semantic Kernel, Vertex AI, Azure OpenAI, AWS Bedrock, Lang Graph, 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

• 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

• 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

• BA/BS plus at least 10 years of relevant architecture experience or demonstrated equivalency of experience and/or education
• At least 4 years of experience in ML or AI systems design and architecture
• Proven expertise in designing and deploying enterprise‑grade genAI, RAG models, agentic AI, and ML pipelines.
• Working knowledge/experience with interoperability protocols such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) for cross‑platform agent communication.
• Experience designing/implementing solutions with agentic frameworks (e.g., Lang Chain, Azure AI Agent Services, n8n, Autogen, etc.).
• Working knowledge of AI Gateway implementation for enforcing guardrails, monitoring, and centralized model access control.
• At least 3 years of experience building AI solutions in AWS or equivalent
• Ability to build AI POCs and design for enterprise production

• Excellent collaboration and communication skills are key
• Must be comfortable engaging with key stakeholders and IT top‑level leadership
• Proven ability to lead and influence cross‑functional teams, including software engineer teams and software product managers
• Demonstrated ability to stay on top of AI trends and best practices

• Understanding of MLOps and Dev Ops practices including CI/CD for models, observability, and rollback Git Hub, Git Hub Actions
• CI/CD pipelines using YML, AWS Cloud Formation, Terraform
• Is intellectually curious in order to keep on top of new concepts in AI/ML, trends, and best practices
• Containerization tools like Kubernetes and Docker
• Programming languages/frameworks including C#, Python, JavaScript, JSON
• Azure Dev Ops for recording and tracking of Epics, Features…