Civil & Structural Engineering Task Lead – AI Projects

• Review engineering tasks end to end, including problem statements, structural and geotechnical models, load cases, simulation data, computational environments, reference solutions, and automated tests.
• Validate tasks covering structural analysis, finite-element analysis (FEA), earthquake and wind engineering, structural dynamics, geotechnical modeling, hydraulics, hydrology, transportation, and infrastructure systems.
• Ensure tasks require meaningful, multi-step engineering reasoning and reflect real-world civil and structural engineering workflows.
• Verify technical correctness across units, equilibrium, boundary conditions, load combinations, design codes, numerical stability, convergence, and safety factors.
• Validate computational models, solvers, dependencies, and simulation outputs for accuracy and reproducibility.
• Review automated graders to ensure they assess meaningful engineering outputs, including forces, deflections, drifts, settlements, factors of safety, flow rates, and structural performance.
• Identify incorrect assumptions, technical errors, unsuitable tolerances, and opportunities to bypass genuine engineering analysis.
• Provide actionable technical feedback and track task revisions through completion.
• Mentor and support 5–10 trainers, allocate work, monitor quality and productivity, and resolve technical blockers.
• Establish and maintain quality standards, technical documentation, and best practices across task development.

• PhD, postdoctoral experience, or equivalent advanced technical expertise in Civil Engineering, Structural Engineering, Geotechnical Engineering, or a closely related discipline.
• Strong programming skills in Python, C/C++, Julia, Fortran, or MATLAB/Octave.
• Proficiency working in Linux and command-line environments.
• Hands-on expertise in at least one major area, such as structural analysis, FEA, earthquake engineering, geotechnical modeling, or hydraulic/hydrological modeling.
• Strong understanding of engineering principles, numerical methods, simulation workflows, and computational model validation.
• Working knowledge of relevant engineering design standards, such as ASCE 7, ACI, AISC, Eurocodes, or IS codes.
• Experience reviewing complex technical work, engineering simulations, research outputs, or computational models.
• Strong analytical judgment and the ability to identify engineering inaccuracies, edge cases, and flawed assumptions.
• Experience mentoring, reviewing, or leading small technical teams.
• Excellent written communication skills for technical feedback and documentation.