Software Engineer - Datacenter/Power Systems
External
Emerald-ai · Bay AreaPrepare for this interview
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About the role
In this role, you will design real-time telemetry pipelines, integrate with datacenter power and compute systems, and implement control and optimization logic that dynamically adjusts workloads based on grid and infrastructure conditions. This role bridges IT and OT environments - turning raw operational data into safe, reliable, production-grade control systems. As an early engineering hire, you'll shape system architecture, own projects end-to-end, and work closely across teams to translate real-world constraints into scalable software.
Responsibilities
- Build software modules that interact with datacenters, on-site industrial power systems and the electrical grid
- Architect and implement data ingest pipelines that collect, normalize, and persist high-frequency telemetry from power meters, PDUs, UPS systems, cooling infrastructure, and compute hardware.
- Design fault-tolerant integration layers between IT systems (cloud APIs, databases, orchestration platforms) and OT systems, handling protocol translation and data model definition and mapping.
- Ensure high safety, reliability, and correctness when interacting with real-world energy assets and critical facilities - including behavior in degraded, disconnected, or split-brain network states.
- Collaborate across teams to deliver end-to-end solutions from edge device to control plane.
- Minimum requirements
- 7+ years of software engineering experience, with strong proficiency in Python and/or Rust, Go or C/C++
- Hands-on experience building telemetry ingest pipelines or distributed systems that handle high-volume, time-series data.
- Familiarity with at least one async messaging system: Kafka, RabbitMQ or equivalent
- Exposure to IT or OT systems (SCADA, EMS, BMS, DCIM) and understanding of how data flows between them.
- Preferred requirements
- Direct experience with industrial telemetry protocols: Modbus TCP/RTU, DNP3, OPC-UA, BACnet, or SNMP.
- Familiarity with time-series databases (InfluxDB, TimescaleDB, Prometheus) or industrial historian platforms (AVEVA PI / OSIsoft, Ignition).
- Experience with Kubernetes, containerized deployments, or HPC job scheduling in datacenter environments.
- Background in power systems, energy markets, microgrids, or datacenter infrastructure (power distribution, cooling, UPS, PDUs).
- Understanding of control system design patterns: PID loops, state machines, setpoint control, or demand response logic.
- Experience with edge compute runtimes or constrained environments where low-latency, reliable local execution matters independent of cloud connectivity.
- Familiarity with optimization algorithms or energy management strategies (load shifting, peak shaving, curtailment) a plus
Benefits
Additional Information
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/ .
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