AI/ML Lead (Agentic AI)

Job: AI/ML Lead (Agentic AI) Location: Richardson, TX 75082 Onsite 2-3x/week (Hybrid) Term: 6-month Contract to Hire Interview Process: Max 2 rounds with the client First round video screen, final round onsite • MUST BE ON VIDEO, NO HEADPHONES AND ABLE TO SHARE THEIR SCREEN • Top Skills/Notes from HM: · Need an AI/ML lead to drive the inflow of AI use cases and streamline processes o Need someone focused on Agentic AI A lot of work in cloud area, multi agents. There is a lot of work around the cloud and getting it to work with multi-agents Key Responsibilities: Agentic AI & Multi‑Agent Systems • Architect, build, and optimize agentic AI systems capable of autonomous reasoning, planning, and tool use. • Design and orchestrate multi‑agent workflows, including communication protocols, coordination strategies, and emergent‑behavior handling. • Develop frameworks enabling agents to interact with cloud services, APIs, and distributed systems. Cloud‑Native AI Engineering • Lead the integration of multi‑agent systems with major cloud platforms (Azure, AWS, or GCP). • Build scalable, reliable, and secure cloud pipelines for training, deployment, and monitoring of AI agents. • Optimize performance across distributed compute environments. Technical Leadership • Serve as a principal‑level technical authority, guiding architecture decisions and long‑term AI strategy. • Mentor engineering teams and collaborate with cross‑functional partners (product, research, platform engineering). • Evaluate emerging technologies and drive innovation in agentic AI and cloud‑based AI infrastructure. Required Qualifications • 8–12+ years of experience in AI/ML engineering, with at least 3+ years at a senior or principal level. • Demonstrated expertise in agentic AI, autonomous agents, or multi‑agent systems. • Strong background in cloud engineering (Azure, AWS, or GCP), distributed systems, and scalable AI infrastructure. • Proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow, JAX, LangChain, etc.). • Experience deploying production‑grade AI systems with complex orchestration requirements. Preferred Qualifications • Experience with LLM‑based agents, tool‑use frameworks, or retrieval‑augmented systems. • Background in reinforcement learning, planning algorithms, or cognitive architectures. • Contributions to open‑source AI agent frameworks. • Prior experience in high‑growth or research‑driven environments.