Lead Engineer - Agentic AI Systems
About The Position
This Lead Engineer – AgenticAI Systems establishes the enterprise strategy, hardware roadmap, and system architecture for AI compute platforms, edge device deployments, and high-performance inference networks. This strategic role owns the reliability, cost optimization, security compliance, and long-term technical direction for all AI infrastructure powering store operations, drive-thru automation, and enterprise analytics. This role is to simplify and improve operations by leading the design of the infrastructure and platform that AI, machine learning, and agentic solutions run on. The primary focus is to lead the design and development of scalable model serving and MLOps/LLMOps systems, direct analysis to right-size and secure infrastructure, and build high quality AI systems that enhance business operations. Another key element of the role is to contribute towards best practices and frameworks to deliver a scalable AI platform using newer tools and technology, while leading a cross-functional team and setting technical direction across multiple concurrent initiatives.
Requirements
- BS in Computer Engineering, Electrical Engineering, or Computer Science with 5+ years of systems engineering, cloud architecture, and infrastructure leadership.
- Demonstrated success architecting multi-region cloud infrastructures, hybrid edge-cloud networks, and large-scale Kubernetes/GKE deployment fleets.
- Exceptional track record of directing complex engineering initiatives, setting technical vision, and negotiating multi-million-dollar technology investments.
- Mastery of heterogeneous compute topologies (GPU/NPU/TPU), low-latency networking, distributed storage, and inference acceleration runtimes.
- Proficient in the use of a variety of software applications including Python, Kubernetes/containerization tools, and cloud technologies (GCP, Azure, or AWS).
Nice To Haves
- Master’s degree in computer science or a related field is preferred.
- Previous experience in the food service or related industry is preferred.
Responsibilities
- Define enterprise technical strategy, hardware roadmaps, and deployment architectures for distributed AI compute infrastructure, cloud platforms, and store-level edge fleets
- Establish enterprise system standards for reliability , disaster recovery, hardware security , and compute cost governance.
- Lead architectural spikes, capacity planning, and system benchmarking for next-generation AI workloads, multimodal models, and local edge inference.
- Partner with Enterprise IT, Security and cross function teams, and Hardware Vendors to design network topologies, edge hardware specifications, and secure API gateways
- Drive technical evaluations, vendor selection, and SLA negotiations for cloud infrastructure providers, GPU vendors, and edge hardware manufacturers
- Provide overall technical oversight, architectural review, and engineering mentorship across infrastructure and AI teams.
Benefits
- parental leave
- free EAP sessions
- company 401k match
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What This Job Offers
Job Type
Full-time
Career Level
Senior
