You will own the end-to-end UX and UI design process, from problem definition to product launch. You will collaborate with strategists, engineers, and clients to create intuitive, data-heavy, and AI-integrated solutions.
You will own the end-to-end cloud infrastructure on Azure, including architecture, scaling, and reliability as the platform transitions to enterprise production. Additionally, you will establish security, disaster recovery, and infrastructure-as-code practices while managing vendor relationships and cloud costs.
You will lead and grow the engineering team while remaining hands-on with code, PR reviews, and architectural guidance. Additionally, you will establish the process and compliance foundation required for SOC 2 and ISO certifications as the platform scales.
The Lead AI Engineer will design and deploy production-grade agentic systems that execute real-world actions with human-in-the-loop controls. They will own the end-to-end agentic function, including architecture, retrieval engineering, and the growth of the technical team.
Design, build, and maintain scalable production-grade data pipelines and platforms to power AI/ML models and agentic workflows. Collaborate with product and engineering teams to translate ambiguous requirements into robust data solutions and optimize workload performance.
Lead and grow the engineering team while architecting a core AI-powered identification and commerce platform for the industrial aftermarket. Own the technical vision, data infrastructure, and mobile-first product experience from MVP to enterprise scale.
Design, build, and scale backend services and APIs to power new venture products. Collaborate on cloud infrastructure and DevOps practices to ensure operational excellence and performance.
Design, train, and deploy AI/ML systems focusing on computer vision and LLM-powered workflows for industrial applications. Translate ambiguous business problems into production-ready AI solutions and collaborate with cross-functional teams to ship MVPs.
