• Lead a team building the inner dev loop. Own the end-to-end experience from laptop-in-box to first pull request: workstation imaging and configuration, privilege and access workflows, enterprise connectivity, developer tooling, and the AI-powered development environment that ties it all together. • Turn "weeks to onboard" into "ready in an hour." The benchmark is real: a developer receives their machine, opens it, and is writing code for their team within their first hour. Your team designs and builds the systems that make that possible at enterprise scale. • Make agentic development tools a first-class citizen. AI coding tools aren't a plugin someone installs later—they're part of the standard environment your team ships. You also ensure developers actually know how to use them well: the workflows, the review patterns, the practices that separate real productivity gains from novelty. • Lead by building. This is not a program management role. You write code, review code, and architect solutions alongside your team. Your credibility comes from what you ship. • Engage deeply with program teams. Your team's work only succeeds if it fits how real engineering teams operate. You stay connected to 3–5 active programs, understand their constraints, and bring those lessons back to improve what you're building. • Drive measurable impact. Success shows up in the metrics: onboarding time collapses, developer satisfaction improves, AI tool adoption climbs, and teams spend less time wrestling with their environment and more time delivering mission software. • Stay ahead of the curve. Continuously evaluate emerging tools and practices—in workstation management, developer environments, and agentic development—and incorporate what's worth adopting into the enterprise standard.

• Design and implement highly available, scalable backend services and APIs that orchestrate complex procurement workflows • Architect resilient service designs and data models that handle high-volume transaction processing • Continuously improve reliability, performance, and scalability through profiling, observability, and load testing • Implement comprehensive security, data protection, and fault-tolerance patterns • Build and optimize asynchronous task processing pipelines for automated procurement decisions • Design caching strategies, database optimization, and service orchestration patterns • Build, test, and ship user-facing web experiences with high performance and accessibility • Contribute in architecting and designing scalable frontend architecture • Own entire features from specification to shipping • Collaborate with product managers and designers to shape solutions and deliver iteratively • Participate in code reviews, raise engineering standards, and reduce technical debt through pragmatic refactors • Mentor junior developers and help establish coding standards and best practices.

• Build, maintain, and improve web applications using modern component architecture patterns and the frameworks and languages relevant to your product area • Use agentic development tools (Claude Code, OpenAI Codex, Cursor, and similar) as standard instruments in your workflow — generating, reviewing, and iterating on code through AI-driven workflows) • Collaborate with Product and Design to translate wireframes and user stories into polished, accessible, and performant interfaces • Participate in code reviews, contributing thoughtful feedback and maintaining a high standard for frontend craft • Contribute to CI/CD pipeline configuration using Azure DevOps for frontend build, test, and deployment workflows • Monitor frontend performance and user experience using Azure App Insights and proactively surface and resolve issues • Stay current with frontend ecosystem developments, browser capabilities, and emerging AI/UX patterns

• Optimize load profiles across multiple classes of devices including thermostats, home batteries, and EVs. • Develop and productionize algorithms and models using machine learning and statistical techniques. • Analyze diverse datasets such as device temperature, energy consumption, user interactions, grid carbon emissions, weather, and energy markets to inform product direction and algorithm design. • Show significant ownership of the algorithms team’s software architecture. • Collaborate with Product, Product Design/UX, Operations, and Engineering to define and deliver impactful features. • Design and lead implementation of projects up to ~1 quarter long. • Help clarify ambiguous problems and shape solutions that balance technical feasibility and business needs. • Participate in system design within the Energy Intelligence team. • Work across our stack: Python, PostgreSQL, Prefect, AWS/GCP (CDK, ECS/EKS, RDS, Redshift, S3, etc.), Apache, Git, and Jira. • Uphold high standards in code quality, testing, security, observability, and operational excellence. • Foster a collaborative and efficient engineering culture, reducing complexity and improving development processes.