Product Manager – AI & Cloud Platform (Intern) at Neosurge Money This is an Independent Consultant / IC Only Neosurge Money (acting as hiring facilitator)- You'll not be working on Neosurge products About the Role We’re searching for an experienced Product manager to guide the evolution of a high-performance AI and Cloud Compute Platform used by engineering and ML teams. You will work directly with founders, engineering leaders, and early customers to shape a platform built for running complex workloads, model pipelines, and cloud-native services at scale. This is a consulting position—you’ll collaborate with our client as an independent contributor. You will not be working on Neosurge Money’s own products. What You’ll Drive Product Vision & Planning Define and iterate the platform roadmap for compute, orchestration, model lifecycle, and developer tooling. Convert customer and technical insights into clear product deliverables, milestones, and release sequencing. Execution & Delivery Work day-to-day with engineering: refine epics, manage the backlog, plan sprints, and ensure delivery quality. Establish product processes—review cycles, documentation, prioritization frameworks, and ongoing improvements. AI/ML & Cloud Platform Ownership Shape features across GPU scheduling, workload management, Kubernetes-based services, and platform observability. Understand the full ML workflow: data prep, training, model deployment, and pipeline automation. ** Customer Engagement** Join calls with engineering teams, ML users, and strategic partners to capture needs and validate product direction. Support adoption by improving onboarding, simplifying workflows, and building helpful product enablement resources. Internal & External Collaboration Work with sales to position the platform clearly and support proof-of-value discussions. Contribute to lightweight thought leadership—use cases, best practices, and practical guidance for teams using the platform. What Makes You Successful in This Role Strong track record shipping technical products, ideally in cloud platforms, devtools, or AI infrastructure. Familiarity with: Kubernetes, containers, and distributed systems Compute orchestration and multi-tenant architectures ML engineering workflows and MLOps practices Monitoring, logs, tracing, and platform reliability Ability to take ownership end-to-end—from idea to working product. Confident communicator, comfortable interacting with engineers, customers, and commercial teams. Curious about the evolving AI ecosystem and able to connect market trends with product strategy. Comfortable working autonomously as a consultant and managing priorities without heavy structure.