• Develop and improve accurate and robust energy forecasting models • Develop and improve control and optimization algorithms • Design, write, test, and deploy production-grade code for mission-critical forecasting and optimization products and related algorithms • Build and use tools and processes to monitor and assess the quality of operational forecasting and optimization models • Translate data from one of the largest distributed energy datasets in the electricity industry into actionable insights for electric utilities and other energy industry stakeholders • Provide guidance to other engineers and scientists regarding machine learning, forecasting and optimization methods • Present results clearly to internal and external stakeholders • Collaborate closely with stakeholders inside and outside of EnergyHub including Data Engineering, Client Success, Marketing, Sales, Product, and Market Development teams • Other duties as assigned

• Own the full lifecycle of GTM-Engine projects – from discovery and system design to execution and measurable pipeline impact. • Translate complex business goals into actionable technical architectures (automations, integrations, workflows). • Lead technical validation and client alignment during both sales and delivery phases to ensure long-term success. • Design and standardize high-performing signal workflows, enrichment processes, and outbound frameworks. • Integrate and optimize tools such as clay, teamfluence, lemlist or instantly to ensure system scalability. • Evaluate and operationalize new data sources (e.g. ad intent, firmographic APIs, product usage signals). • Build and maintain internal GTM knowledge infrastructure – including playbooks, templates, and Loom walkthroughs. • Establish delivery standards and best practices to align client expectations with capacity and system complexity. • Mentor junior GTM engineers and working students to ensure skill development and process consistency. • Identify “winning use cases” and translate them into repeatable frameworks that scale across clients. • Collaborate with leadership on service design, new offerings, and GTM methodology refinement.

• Lead end-to-end growth initiatives (referrals, ambassadors, activation): design, build, launch, measure, and iterate • Design and execute A/B experiments on acquisition, activation, and retention • Build automations and custom integrations (APIs, scripts, no-code/low-code) without relying on the product roadmap • Define, instrument, and monitor key metrics: MAUs, K-factor, CAC, LTV, referral rate • Analyze funnels and identify bottlenecks and growth opportunities • Propose and maintain an independent growth roadmap, communicating results to the team

• Design, develop, and maintain scalable services that support the diverse activities of a high-throughput laboratory. • Develop both front-end and back-end applications. • Implement and manage CI/CD pipelines using GitLab. • Develop comprehensive unit tests to ensure high code quality. • Collaborate closely with end-users and product managers to iterate on requirements and deliverables. • Optimize architecture and infrastructure on the AWS cloud platform for performance, scalability, reliability, and cost-effectiveness. • Proactively monitor system performance, troubleshoot issues, conduct thorough root cause analysis, and implement enhancements to improve efficiency and reliability. • Stay current with emerging technologies and best practices in software engineering and actively contribute to continuous improvement initiatives. • Be the technical lead and mentor more junior engineers. • Visit the lab in San Carlos, CA occasionally to facilitate direct observation of the software in the lab and obtain real-time user feedback.