About Emerald AI

We’re at a pivotal moment for AI and energy. Demand for compute is skyrocketing, but power constraints are becoming a critical bottleneck. Emerald AI sits at the intersection of these two worlds, enabling AI data centers to scale without overwhelming the grid.

Our Emerald Conductor software platform makes data centers flexible and responsive, allowing them to adjust power usage dynamically. This unlocks massive AI growth without major new infrastructure, while also strengthening the grid and supporting the expansion of renewable energy.

We’re a team of experts across AI, cloud, software, and energy—on a mission to scale AI sustainably. We’re backed by leading investors and partners including Radical Ventures and NVIDIA.

Learn more about our vision, team, and backers at https://www.emeraldai.co/.

About the Role

Emerald AI is building the software platform that enables AI infrastructure to intelligently orchestrate compute in response to power availability, grid conditions, and operational constraints. We are looking for a Senior Product Manager to own the core platform powering our technology.

This is a highly technical product role where you'll work alongside engineering to define platform capabilities, translate complex customer and technical requirements into clear product direction, and drive execution from concept through production. You'll operate at the intersection of distributed systems, AI infrastructure, cloud platforms, and data center software.

If you enjoy solving deeply technical infrastructure problems, partnering closely with engineers, and building products from first principles, we'd love to talk.

Key Responsibilities

Own the roadmap for Emerald AI's core compute platform, including workload orchestration, control plane capabilities, APIs, telemetry, and platform observability.

Define product capabilities that intelligently orchestrate AI workloads across distributed compute infrastructure while ensuring reliability, scalability, and performance.

Partner closely with engineering to translate product strategy into clear, technically rigorous requirements and execution plans.

Drive the evolution of platform services, including workload power profile simulation, NVIDIA DSX integrations, and telemetry pipelines.

Work directly with customers and internal stakeholders to understand infrastructure workflows, operational challenges, and platform requirements.

Lead platform releases from planning through deployment, ensuring high quality, operational readiness, and a seamless customer experience.

Prioritize platform investments by balancing customer value, technical complexity, and long-term architectural goals.

Minimum requirements

5+ years of product management experience building infrastructure software, cloud platforms, or distributed systems.

Experience delivering highly technical platform products, including APIs, control planes, or developer-facing infrastructure.

Demonstrated ability to write exceptionally clear product requirements, technical specifications, and acceptance criteria.

Proven ability to drive ambiguous technical problems from concept to execution while balancing customer needs and engineering constraints.

Excellent prioritization, written communication, and cross-functional leadership skills.

Comfortable operating in a fast-moving, early-stage startup environment and partnering closely with senior engineering teams.

Preferred requirements

Experience with AI infrastructure, GPU scheduling, or large-scale compute orchestration.

Experience building platform or infrastructure software products.

Familiarity with observability platforms, telemetry pipelines, monitoring systems, or infrastructure instrumentation.

Experience with Kubernetes, workload schedulers (e.g., Slurm), or distributed compute platforms.

Exposure to NVIDIA's AI software ecosystem, including NVIDIA DSX and related technologies.

Experience with power-aware scheduling, workload optimization, or data center infrastructure is a plus.

What We Offer

Make an impact. Solve the AI power bottleneck and shape how data centers scale sustainably.