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. You will help us translate real process safety workflows into product requirements and validation checks: Define how HAZOPs are run in practice across downstream projects and what “good” looks like Review and validate HAZOP readiness: P&IDs, cause and effect, control narratives, safeguarding completeness Capture how deviations are generated, recorded, and resolved across disciplines Map where safety review rework happens and what typically causes it (missing info, inconsistent tagging, late design changes) Translate common safeguards and recommendations into repeatable checks across engineering packages Clarify interfaces with Process, I&C, Mechanical, Electrical, and Operations perspectives Identify which steps are repetitive vs which require real engineering judgement Your experience will help define the checks, workflows, and product requirements that let software take on the repetitive parts, with engineers in control.
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Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed