AI Architect Agentic Generative AI

1 week ago


Dallas, TX, United States SelectMinds Full time

Benefits:

Oppurtunity for Advancement

Hybrid

Long Term

Job Title: Agentic AI Solution Architect Location: Dallas, TX (hybrid/remote flexibility possible) Department: AI Delivery

Role Summary: You will design, architect, and lead the deployment of agentic (autonomous, multi-agent) AI systems acrossthe Client's Operations, Systems, and Customer-facing domains. You'll bridge business goals, existing infrastructure, and next‑gen AI capabilities to deliver high-impact solutions aligned with Southwest's strategy.

Key Responsibilities -

Define end-to-end architecture for agentic AI systems (multi-agent orchestration, coordination, planning, feedback loops) - Evaluate, select, and integrate AI frameworks, platforms, and infrastructure components.

Collaborate with business units (operations, crew scheduling, customer service, disruption management) to map use cases to agentic AI designs.

Define interfaces, APIs, data flows, governance and security models for agents to interact with legacy systems.

Establish architecture patterns, best practices, design principles for autonomous agents in an enterprise setting.

Lead technical reviews, prototype validation, and iteration cycles.

Mentor/coach engineering and AI teams on agentic design and scalable AI deployment.

Stay abreast of research in autonomous agents, reinforcement learning, self‑adaptation, and inject innovations into Southwest's roadmap.

Requirements / Must-Haves

Bachelor's or Master's in Computer Science, AI, Systems Engineering, or related.

Strong background in AI/ML, especially reinforcement learning, multi-agent systems, planning, feedback control.

Proven experience in solution architecture for large-scale distributed systems, microservices, event-driven / streaming architecture. Experience building or integrating autonomous or semi-autonomous agents or intelligent systems - Proficiency with modern cloud platforms (AWS, Azure, GCP) and AI infrastructure (model serving, orchestration, autoscaling).

Understanding of data pipelines, data governance, security, APIs, and systems integration - Excellent communication — you'll translate between technical teams and business stakeholders .

Track record of delivering AI systems into production

Preferred / Nice-to-Haves

Familiarity with AI governance, explainability, monitoring, and safety

Knowledge of reinforcement learning libraries (e.g. RLlib, Ray, OpenAI frameworks)

Experience with observability, continuous learning pipelines, adaptation in deployed agents

Flexible work from home options available.



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