Software Engineer – Grid Services

Jobtailor; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor in San Francisco seeks an experienced software engineer to design and build integrations with ISOs/RTOs, utilities, and demand response platforms. You will implement algorithms to dispatch data center resources and develop forecasting models for demand, prices, and grid conditions.

The role requires strong experience with distributed systems, cloud platforms, and data pipelines, along with excellent communication skills to collaborate across teams.

Qualifications

• 7+ years of software engineering experience building production systems in Python.
• Strong experience designing and operating reliable, distributed software systems where correctness and availability are critical.
• Experience with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker/Kubernetes), and CI/CD pipelines.
• Experience building data pipelines and working with large-scale operational datasets.
• Familiarity with SQL and modern data engineering practices.
• Experience in electric utilities, ISOs/RTOs, wholesale electricity markets, demand response, or adjacent energy systems.
• Excellent communication and collaboration skills.
• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related quantitative field.

Responsibilities

• Design and build software integrations with ISOs/RTOs, utilities, aggregators, and demand response platforms.
• Develop optimization and control algorithms that determine when and how data center resources including compute workloads, on-site generation, and storage are dispatched in response to grid signals.
• Build forecasting models for electricity demand, data center load, prices and grid conditions to support market participation and dispatch decisions.
• Translate wholesale market and demand response program rules including capacity accreditation, baselines, measurement & M&V, settlement, and compliance into operational software.
• Build reliable data pipelines that ingest, validate, and process real-time operational and market data.
• Own software services from design through deployment, monitoring, and long-term operation.

Skills

Python

Distributed systems

Data pipelines

SQL

Communication

Education

Bachelor's/Master's/PhD in CS, EE or related quantitative field

Tools

AWS

GCP

Azure

Docker

Kubernetes

CI/CD

Job description

Responsibilities

• Design and build software integrations with ISOs/RTOs, utilities, aggregators, and demand response platforms.
• Develop optimization and control algorithms that determine when and how data center resources including compute workloads, on-site generation, and storage are dispatched in response to grid signals.
• Build forecasting models for electricity demand, data center load, prices and grid conditions to support market participation and dispatch decisions.
• Translate wholesale market and demand response program rules including capacity accreditation, baselines, measurement & verification (M&V), settlement, and compliance into operational software.
• Build reliable data pipelines that ingest, validate, and process real-time operational and market data.
• Own software services from design through deployment, monitoring, and long-term operation.

Requirements

• 7+ years of software engineering experience building production systems in Python
• Strong experience designing and operating reliable, distributed software systems where correctness and availability are critical
• Experience with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker/Kubernetes), and CI/CD pipelines
• Experience building data pipelines and working with large-scale operational datasets
• Familiarity with SQL and modern data engineering practices
• Experience in electric utilities, ISOs/RTOs, wholesale electricity markets, demand response, or adjacent energy systems
• Excellent communication and collaboration skills
• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related quantitative field