Principal AI Architect

DIRECTV•El Segundo, CA

1d•$134,363 - $244,036•Remote

About The Position

The Principal AI Architect is a senior individual contributor who defines, designs, and evolves enterprise-grade Generative AI and AI-driven architectures aligned with DIRECTV’s strategic business objectives. The role provides technical leadership and architectural authority across GenAI, AI/ML platforms, and enterprise systems, with an emphasis on scalable, secure, reusable, and future-ready solutions. The architect partners with Application Architects, Data Architects, Platform Engineers, product teams, and business stakeholders to integrate Generative AI into enterprise solutions while maintaining architectural governance. The position defines advanced architectures for Model Context Protocol (MCP), multi-agent systems, and agent-to-agent orchestration. It also establishes reusable patterns and standards, guides delivery teams, and shapes the technical direction and long-term sustainability of AI-enabled solutions across DIRECTV. This is a remote position located anywhere in the United States except Alaska. The position has no supervisory responsibilities. A background check may be required because the job involves routine access to DIRECTV and customer proprietary data.

Requirements

Bachelor of Science degree in Computer Engineering, Computer Science, Applied Science, Electrical Engineering, or Math, or equivalent experience.
5–7 years of experience in Enterprise and Solution Architecture roles required.
Deep expertise in Generative AI and AI/ML architectures, including LLM-based systems, RAG, vector stores, orchestration layers, and AI platform design.
Proven experience designing multi-agent systems, agent orchestration frameworks, or context-driven GenAI platforms in enterprise environments.
Demonstrated ability to design secure, scalable, and resilient enterprise architectures.

Nice To Haves

8 or more years of experience in Enterprise and Solution Architecture roles.
Experience applying Generative AI in enterprise-scale production environments.
Familiarity with Media and Telecom industry architectures and constraints.
Experience developing or designing PCI-compliant application architecture.
Hands-on architectural experience with Salesforce, MuleSoft, Genesys, and enterprise GenAI platforms or frameworks.
Knowledge of AI governance, responsible AI practices, data privacy, and regulatory considerations.

Responsibilities

Serve as an enterprise technical authority for Generative AI and AI-driven architecture, providing hands-on architectural leadership as an individual contributor.
Drive GenAI strategy and solution design by evaluating and applying technologies such as LLMs, RAG, AI agents, vector databases, prompt engineering frameworks, and model orchestration platforms.
Architect and govern MCP implementations, defining how context, memory, tools, policies, and guardrails are structured, versioned, and securely shared across AI workflows.
Design and lead multi-agent and agent-to-agent orchestration architectures for autonomous task decomposition, collaboration, escalation, and decision-making.
Define orchestration strategies for LLMs, agents, tools, workflows, and downstream systems while balancing performance, cost, reliability, observability, and maintainability.
Partner with business and product stakeholders to translate business problems into AI-driven solutions, explain technology value propositions, and support business-case development with measurable outcomes.
Lead architectural discovery and design workshops, align AI capabilities with DIRECTV’s strategic goals, and guide teams toward practical, scalable implementations.
Establish reusable AI architecture patterns, reference architectures, and best practices that support adoption, consistency, governance, and risk management.
Ensure architectural flexibility and future-proofing through modular, abstracted designs that accommodate evolving models, vendors, and regulatory requirements.
Influence enterprise standards for AI architecture, modeling practices, design principles, security, data governance, and responsible AI usage.
Provide architectural guidance to delivery teams, review designs, validate implementation approaches, and ensure adherence to enterprise and AI-specific standards.