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About the Role

Candid is building the AI layer for EPCs, using AI to reduce manual effort in preconstruction engineering by automating document understanding, consistency checks, and repetitive workflow steps. Our goal is to make preconstruction 10x faster without sacrificing engineering quality.

Responsibilities

• Translate real mechanical workflows into product requirements and validation checks.
• Define how equipment scope is developed and validated during FEED.
• Review and validate mechanical content across datasheets, vendor packages, and discipline handoffs.
• Create repeatable checks that catch scope gaps and inconsistencies early.
• Map where mechanical rework happens and what typically causes it.
• Clarify interfaces with Process, Piping, I&C, and Electrical.
• Identify which steps are repetitive versus those requiring engineering judgment.

Requirements

• 7+ years at an EPC, PMC, or owner operator.
• Strong understanding of FEED and early detailed design mechanical workflows.
• Experience creating and reviewing equipment datasheets and vendor packages.
• Familiarity with ASME code driven equipment practices and common downstream equipment types.
• Ability to spot inconsistencies across datasheets, P&IDs, and vendor packages.
• Clear understanding of cross discipline dependencies.
• Experience with turbomachinery heavy scopes or packaged systems (Nice to Have).
• Experience taking equipment from FEED into procurement and detailed engineering (Nice to Have).
• Interest in AI or automation (Nice to Have).

Skills

• Mechanical workflows
• Product requirements
• Validation checks
• Equipment scope development
• Datasheet review
• Vendor package review
• ASME code
• Cross discipline dependencies
• AI
• Automation

Experience Level

• 7+ years

Benefits

• Meaningful base + equity
• Unlimited PTO
• Generous health insurance covering medical, dental, and vision
• Health and Wellness Budget ($150/mo reimbursement)

About the Company

• Candid is building the AI layer for EPCs.
• We use AI to reduce the manual effort behind preconstruction engineering by automating document understanding, consistency checks, and repetitive workflow steps across major disciplines.
• Our goal is to make preconstruction 10x faster without sacrificing engineering quality.
• We recently raised $6.5M from top AI and industrial investors (including Schneider Electric and Meta’s Chief AI Scientist).
• Our team includes engineers from MIT, Carnegie Mellon, major LNG and power projects, and leading EPCs.