Lead Artificial Intelligence Engineer - Hybrid in Dallas, TX NOT

Lead AI Engineer – Agentic & Generative AI

Are you passionate about building the future of AI? We are seeking a Lead AI Engineer to drive the strategy, architecture, and delivery of Agentic and Generative AI solutions across a fast-growing technology portfolio. In this highly visible leadership role, you will architect scalable AI systems, mentor engineering teams, and partner with executives and product leaders to deliver innovative, production-grade AI experiences.

• Lead the end-to-end architecture and technical roadmap for AI products and platforms, including LLM strategy, RAG, multi-agent systems, and workflow orchestration.
• Design scalable AI solutions leveraging foundation models, multimodal AI, retrieval systems, semantic search, and knowledge graphs.
• Build reusable AI capabilities, including shared RAG frameworks, SDKs, prompt standards, and agentic backend services.
• Establish best practices for AI observability, governance, evaluation, logging, and responsible AI development.
• Mentor and guide AI Engineers, ML Engineers, and Data Scientists, conducting architecture and code reviews while fostering engineering excellence.
• Partner with product, design, and business leaders to identify high-impact AI opportunities, define roadmaps, and deliver measurable outcomes.
• Drive performance, reliability, and cost optimization through model routing, caching, infrastructure scaling, and build‑vs‑buy decisions.
• Ensure AI solutions meet security, privacy, compliance, and governance standards.

• 8+ years of experience in Software Engineering, ML Engineering, or Data Science, including:
• 3+ years of hands‑on experience with Applied AI/LLMs
• 2+ years in a technical leadership or lead engineering role
• Proven experience architecting and deploying production‑scale AI systems using:
• LLMs, prompt engineering, function/tool calling, and multi‑agent workflows
• RAG architectures, vector databases, and retrieval optimization
• AI observability, monitoring, and evaluation frameworks
• Strong experience designing and operating cloud‑native systems in AWS, GCP, or Azure.
• Hands‑on experience with Docker, Kubernetes, CI/CD pipelines, and distributed systems.
• Experience using AI coding assistants such as Cursor, Windsurf, or Codex.
• Demonstrated success leading technical initiatives, mentoring engineers, and balancing speed, quality, and cost tradeoffs.
• Excellent communication skills with the ability to explain complex AI concepts to both executives and technical stakeholders.

• Experience with multimodal AI, real‑time agents, voice AI, or streaming interactions.
• Familiarity with AI evaluation frameworks such as OpenAI Evals or Lang Smith.
• Experience with data platforms, event streaming (e.g., Kafka), feature stores, or data lakes/warehouses.
• Experience designing AI systems in regulated or privacy‑sensitive environments.
• Background building organizational AI strategies, engineering standards, and AI capability roadmaps.

This is an opportunity to shape the future of Agentic AI and Generative AI at scale, influence technical strategy, and build next‑generation intelligent products that deliver meaningful business impact.

Ready to lead the next wave of AI innovation? Apply today and help define the future of intelligent systems.