Job Opportunities API

What We Do  At Terabase Energy, we believe that digitalization and automation will drive the next wave of innovation and cost reduction in large-scale solar energy. To fully unlock the potential of this opportunity, Terabase is developing an interconnected software and construction automation platform. We work alongside project developers, owners, and engineering & construction firms to support the design, optimization, and construction of huge solar projects around the world.  Our team is a blend of solar industry veterans and newbies, thought-leaders, dreamers, software, electrical, and mechanical engineers, coders, product managers, project managers, and sales and marketing professionals. We are based in Northern California, with several other offices in the United States and worldwide. If this piques your interest, we'd love to hear from you.  About the Role We are seeking a Process Improvement Manager to sit at the intersection of EPC domain expertise and AI system design. This role is responsible for translating complex, real-world EPC and construction workflows—particularly engineering, estimating, procurement, and construction item processes—into precise specifications that AI engineers can implement as high-impact agents.  You will work directly with construction professionals (estimators, engineers, project managers) and software engineers to map how work actually gets done today, identify bottlenecks on the critical path, and convert those insights into clear, testable AI agent specifications that compress schedules and reduce execution risk.  This is not a theoretical process role—it is hands-on, workflow-level, and outcome-driven.  Key Responsibilities  1. EPC Process Discovery & Mapping  Decompose end-to-end EPC workflows with a focus on conceptual engineering, estimating, detailed design, long-lead procurement, contracting and construction.  Produce very granular process maps, swim-lane diagrams, and value stream maps that reflect real execution—not idealized procedures.  Identify handoffs, rework loops, decision gates, data dependencies, and critical path constraints across disciplines.  Maintain a system-level view of how engineering outputs unlock procurement, and construction activities   2. AI Opportunity Identification  Analyze mapped workflows to pinpoint schedule-critical and labor-intensive tasks where AI can deliver immediate value.  Prioritize opportunities based on schedule compression, feasibility, risk reduction, and scalability (e.g., long-lead release acceleration, engineering iteration reduction).  Partner with technical teams to define short-term vs. long-term AI roadmaps aligned to EPC execution realities   3. Agent Specification & Translation   Translate business workflows into AI agent specifications, clearly defining:  Inputs (documents, data, constraints)  Outputs (decisions, deliverables, recommendations)  Triggers and dependencies  Success metrics and acceptance criteria  Ensure specifications are detailed enough for AI engineers to implement without domain guesswork.  Explicitly document edge cases, failure modes, and human-in-the-loop requirements.  4. Stakeholder Validation & Iteration  Review agent concepts and prototypes with stakeholders.  Validate that agent behavior aligns with how EPC teams actually work under schedule pressure.  Iterate specifications based on field feedback to ensure adoption and measurable impact.  Requirements Required  Ba