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Agentic AI Solution Architect

Agentic AI Solution Architect

Select Minds LLCDallas, TX, US
10 days ago
Job type
  • Full-time
Job description

Job Description

Job Description

Benefits :

  • Oppurtunity for Advancement
  • Hybrid
  • Long Term

Job Title : Agentic AI Solution Architect

Location : Dallas, TX (Day 1 Onsite)

Interview : In-person

Role Summary :

We are seeking an Agentic AI Solution Architect to design, architect, and lead the deployment of autonomous multi-agent AI systems across mission-critical operations, customer-facing platforms, and enterprise IT ecosystems. This role bridges business priorities, large-scale infrastructure, and next-generation AI capabilities to deliver high-value, safe, and scalable solutions. You will work closely with stakeholders across operations, IT, and customer experience to turn business challenges into working agentic AI designs ready for production.

Key Responsibilities :

  • Architect end-to-end agentic AI ecosystems with orchestration, planning, and autonomous execution.
  • Design multi-agent workflows for disruption management, crew scheduling, predictive maintenance, and customer rebooking.
  • Integrate LLM agents with enterprise and systems (APIs, databases, IoT, crew management platforms).
  • Define interfaces, APIs, data flows, governance, and security models for safe agent-to-system interactions.
  • Establish architecture patterns, best practices, and design principles for scalable agentic AI deployments.
  • Implement governance and safety guardrails, including escalation frameworks and human-in-the-loop oversight.
  • Lead technical reviews, prototyping, validation, and iteration cycles to refine AI solutions.
  • Mentor engineering and AI teams on agentic design, RAG patterns, and scalable AI deployment.
  • Track emerging research in multi-agent systems, reinforcement learning, and self-adaptive AI, and apply relevant innovations.

    • Required Skills

  • 10+ years in IT / AI Solution Architecture, with 23 years in LLM / Agentic AI system design.
  • Hands-on experience with LangChain, AutoGen, CrewAI, Azure AI Agent Framework.
  • Strong expertise in RAG (Retrieval-Augmented Generation), embeddings, and vector DBs (Pinecone, Weaviate, FAISS).
  • Proven track record in architecting distributed systems, microservices, and event-driven / streaming platforms.
  • Cloud expertise : AWS, Azure, or GCP AI / ML platforms (model serving, orchestration, autoscaling).
  • Strong integration background in APIs, event-driven architectures, and enterprise system interoperability.
  • Experience delivering AI systems into production with attention to governance, observability, and continuous learning.
  • Excellent communication skills for bridging technical teams and business stakeholders.

    • Preferred / Nice-to-Haves

  • Familiarity with AI governance, monitoring, explainability, and safety frameworks.
  • Experience with reinforcement learning libraries (Ray, RLlib, OpenAI frameworks).
  • Exposure to digital twin simulations for testing and validating agent behaviors
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