Senior Engineer–AI Sustainable building design

WSP in India; Dadri; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

WSP in India is seeking an AI Engineer – Built Environment / Sustainability to lead AI-driven design and energy analyses for buildings. You will develop ML models, calibrate energy simulations, and integrate AI into BIM workflows with Revit and Rhino.

The role requires 5–10 years of experience in energy modelling, carbon assessment, and building performance simulation, with strong Python and ML framework skills.

Qualifications

• Degree in engineering or a related field with emphasis on energy or sustainability.
• Proven experience in energy modelling, carbon analysis or building performance simulation.
• Strong programming skills and ML framework experience.

Responsibilities

• Develop and implement ML models to optimize building layouts, systems and materials.
• Evaluate design options with multi-objective optimization for energy, carbon, cost and comfort.
• Build and calibrate energy models using simulation tools and AI-augmented approaches.
• Conduct carbon assessments for buildings and infrastructure.
• Analyze energy use and identify improvement strategies for performance.
• Create data pipelines to support AI workflows and simulations.
• Integrate AI models into BIM platforms (Revit, Rhino) and design tools.
• Develop predictive models for building performance and simulate real-world conditions.
• Validate model outputs against real or simulated data.
• Collaborate with architects and engineers to translate AI outputs into practical solutions.

Skills

Python

ML frameworks

Energy modelling

BIM tools

MLOps & data pipelines

Education

Engineering degree

Building Science

Data Science

Tools

EnergyPlus

IES VE

Revit

Rhino

Rhino/Grasshopper

Job description

Job Title: AI Engineer – Built Environment / Sustainability

Responsibilities

• Develop and implement machine learning and generative AI models to optimize building layouts, systems, and materials.
• Apply AI techniques to evaluate multiple design options rapidly and build multi‑objective optimization models considering energy efficiency, carbon, cost, and comfort.
• Build and calibrate building energy models using simulation tools and AI‑enhanced approaches.
• Conduct operational and embodied carbon assessments for buildings and infrastructure.
• Analyze energy consumption and identify strategies to improve performance and efficiency.
• Collect, clean, and integrate diverse datasets (climate, material, energy use, geospatial) and develop data pipelines that support AI/ML workflows and simulation models.
• Integrate AI models into BIM platforms (Revit, Rhino/Grasshopper) and other digital design tools.
• Develop predictive models for building performance (thermal, energy, daylight, ventilation) and use AI to simulate real‑world conditions.
• Validate model outputs against real‑world or simulated performance data.
• Collaborate closely with architects, building services engineers, planners, and sustainability consultants to translate AI outputs into practical, code‑compliant engineering solutions.
• Contribute to design reports, technical submissions, and client deliverables.
• Support client engagements by assessing emerging AI platforms, tools, and technologies relevant to the built environment and sustainability; conduct technology benchmarking and market scans.
• Develop cost‑benefit analyses and business cases for AI adoption, translating technical assessments into client‑ready insights and recommendations.

Qualifications

• Degree in Engineering, Building Science, Environmental Engineering, or Data Science.
• 5–10 years of experience in energy modelling, carbon analysis, or building performance simulation.
• Strong programming skills (Python preferred) and experience with machine‑learning frameworks such as TensorFlow or PyTorch.
• Knowledge of building energy‑modelling tools (e.g., EnergyPlus, IES VE) and familiarity with BIM platforms and digital design tools (Revit, Rhino).
• Understanding of MLOps, data pipelines, and model deployment.

Key Outcomes / Deliverables

• AI‑driven design tools and models integrated into engineering workflows.
• Energy and carbon performance assessments supporting low‑carbon design.
• Optimized building designs balancing sustainability, cost, and constructability.
• Data‑driven insights informing client decisions and regulatory submissions.

Key Skills & Competencies

• Building physics, HVAC systems, and energy performance analysis.
• Lifecycle carbon assessment and sustainability frameworks (e.g., LEED, BREEAM).
• Understanding of AEC workflows, design processes, and regulatory environments.
• Strong analytical and problem‑solving capability.
• Effective communication of complex technical outputs to non‑AI stakeholders.
• Collaborative mindset for multidisciplinary project environments.