Terabase Energy

Terabase Energy

EPC Process Improvement Manager

Berkeley, California, United States · Contract

Sponsorship not specified$150k-$170kDetected 89 days ago
Process ImprovementProcurementSystems EngineeringCommunicationMicrosoft Office

About the role

  • This is not a theoretical process role-it is hands-on, workflow-level, and outcome-driven.

Responsibilities

  • 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.
  • 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.
  • Validate that agent behavior aligns with how EPC teams actually work under schedule pressure.
  • Strong working knowledge of EPC workflows, particularly: Engineering (conceptual → detailed design → construction drawings) Procurement and contracting strategy Schedule and dependency management Proven ability to create clear, structured process documentation from ambiguous real-world inputs.
  • AI engineers can build from your specifications without repeatedly revisiting domain assumptions.

Requirements

  • Required Bachelor's degree in Engineering or equivalent 5+ years' experience in business process design, operations analysis, systems engineering, or EPC project delivery.

Nice to have

  • Career progression
  • Terabase is an equal opportunity employer.
  • We recruit, hire, employ, train, promote, and compensate individuals based on job-related qualifications and abilities.
  • We strongly encourage people of all backgrounds to apply.
  • Principles only.
  • This role is not open to receiving agency candidates, and any contingent submissions will not be considered.
  • Terabase Energy does not utilize third-party recruitment agencies.
  • Please contact our Recruiting team at careers@terabase.energy with any staffing-related inquiries.

Compensation

  • $150k-$170k

Company info

  • 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.

Visa & Work Authorization

  • iminate for any reason including race, color, sex, gender, age, religion or religious creed, national origin, ancestry, citizenship, marital status, sexual orientation, gender identity, gender expression, genetic informa
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This listing is sourced directly from Terabase Energy's careers page and normalized into a canonical job model.