Agentic AI Architect

Title:

Agentic AI Architect

Location:

Dallas or Houston, TX (hybrid: 2 days onsite / 3 days remote)
Duration:
Direct Hire
Compensation: $190K - $220K per year
Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S.

We are seeking a hands‑on Agentic AI Architect with strong expertise in Agentic Workflows, MCP, C#, SQL Server, Angular, and Azure Cloud technologies to architect, design, build, and optimize enterprise‑grade AI platforms. The ideal candidate will have hands‑on experience with modern AI frameworks
, including Agentic Workflows,
MCP,
Semantic Kernel, Kernel Memory, Azure AI Foundry
, and the integration of multiple LLMs in advanced architecture such as Retrieval Augmented Generation (RAG).

This role requires a balance of advanced AI architecture experience,
hands‑on
full‑stack development skills with a forward‑looking mindset on AI‑driven platform development
, ensuring scalability, security, and performance in production systems.

We are offering an opportunity to work with cutting‑edge AI and cloud technologies
.

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

• Define and evolve the enterprise AI platform architecture, breaking down business and functional requirements into scalable, secure, and maintainable technical designs.
• Establish the long‑term architecture runway for AI products, owning POCs, design spikes, and forward‑looking evaluations of emerging technologies—
  including agentic architectures, orchestration frameworks, and tool‑use patterns
  .
• Apply expertise in distributed systems and API design to ensure the platform is robust, observable, and simple to extend.
• Ensure best practices in secure coding, performance optimization, resilience, and lifecycle maintainability.

• Architect and implement enterprise‑grade RAG (Retrieval Augmented Generation) pipelines, including vector search, embeddings, knowledge stores, and LLM orchestration.
• Design and operationalize agentic workflows
  , including multi‑agent collaboration, tool‑calling agents, planner/executor patterns, and automated reasoning loops.
• Build and integrate production‑grade AI agents capable of interacting with external tools, APIs, enterprise systems, and knowledge sources.
• Utilize the Model Context Protocol (MCP) to expose internal tools, datasets, and enterprise APIs to LLMs in a secure, governed manner.
• Integrate and operationalize multiple LLM providers (Azure OpenAI, OpenAI, Anthropic, open‑source models) into production systems.
• Leverage Azure AI services—
  Semantic Kernel
  , Kernel Memory
  , AI Foundry
  , Cognitive Search—to enable intelligent, context‑aware platform capabilities.
• Design, deploy, and optimize cloud‑native AI applications in Azure with emphasis on cost efficiency, observability, resilience, and security.

• Partners with enterprise architects, product managers, developers, and data engineers in an Agile/Scrum environment to ensure architecture aligns with product strategy.
• Provide hands‑on mentorship on AI development patterns—including agent‑building, RAG troubleshooting, prompt design, vector search patterns, and orchestration frameworks.
• Conduct architecture reviews, code reviews, and design sessions to drive engineering quality and consistency.
• Translate business needs into scalable platform capabilities that support long‑term product and enterprise roadmaps.

• Stay current on rapidly evolving AI trends:
  multi‑agent systems, model orchestration, tool‑use protocols, evaluation frameworks, prompt engineering, latency optimization, and AI safety approaches
  .
• Recommend improvements to development, testing, deployment, and estimation processes to increase delivery velocity while maintaining quality and compliance.
• Establish platform‑level governance patterns including architectural guardrails, reusable modules, MCP tool adapters, and standardized agent templates.
• Champion experimentation, rapid…