Senior Engineer–AI Sustainable building design

WSP is looking for Candidate who should hold experience minimum of 5 to 10 years in energy modelling, carbon analysis, or building performance simulation. To partner as an AI Engineer (Built Environment / Sustainability) to develop and apply advanced artificial intelligence techniques to support the design of energy-efficient, low-carbon buildings and infrastructure.

1. AI-Driven Design & Optimization

• Develop and implement machine learning and generative AI models to optimize building layouts, systems, and materials.
• Apply AI techniques (e.g., generative design, optimization algorithms) to evaluate multiple design options rapidly.
• Build multi-objective optimization models considering energy efficiency, carbon, cost, and comfort.

2. Building Energy & Carbon Modelling

• Develop and calibrate building energy models using simulation tools and AI-enhanced approaches.
• Conduct operational and embodied carbon assessments for buildings and infrastructure.
• Analyse energy consumption and identify strategies to improve performance and efficiency.

3. Data Engineering & Integration

• Collect, clean, and integrate diverse datasets (climate, material, energy use, geospatial).
• Develop data pipelines to support AI/ML workflows and simulation models.
• Integrate AI models into BIM platforms (e.g., Revit, Rhino/Grasshopper) and digital design tools.

4. Performance Simulation & Predictive Analytics

• Develop predictive models for building performance (thermal, energy, daylight, ventilation).
• Use AI to simulate real-world conditions (weather, occupancy, operational patterns).
• Validate model outputs against real-world or simulated performance data.

5. Collaboration & Project Delivery

• Work closely with architects, building services engineers, planners, and sustainability consultants.
• Translate AI outputs into practical, code-compliant engineering solutions.
• Contribute to design reports, technical submissions, and client deliverables.

6. AI Strategy, Market Research & Cost-Benefit Analysis

• Support client engagements by assessing emerging AI platforms, tools, and technologies relevant to the built environment and sustainability
• Conduct structured technology benchmarking and market scans (e.g. generative design tools, digital twins, energy optimisation platforms)
• Evaluate technical feasibility, implementation requirements, and integration considerations within existing design and asset workflows
• Develop cost-benefit analyses and business cases for AI adoption
• Translate technical assessments into clear, client-ready insights and recommendations, supporting decision-making at project and portfolio level.
• Strong programming skills (Python preferred) for AI/ML development.
• Experience with machine learning frameworks (TensorFlow, PyTorch, or similar).
• Knowledge of building energy modelling tools (e.g., EnergyPlus, IES VE).
• Familiarity with BIM platforms and digital design tools (e.g., Revit, Rhino).
• Understanding of MLOps, data pipelines, and model deployment.

Key Skills & Competencies

Technical Skills

Domain Knowledge

• 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.

Soft Skills

• Strong analytical and problem-solving capability.
• Ability to communicate complex technical outputs to non-AI stakeholders.
• Collaborative mindset for multidisciplinary project environments.

• Degree in Engineering, Building Science, Environmental Engineering, or Data Science.

• 5 to 10 years’ experience in energy modelling, carbon analysis, or building performance simulation.

• Experience in AI/ML applied to buildings, energy systems, or sustainability is desirable.

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.

BGV:

• Employment with WSP India is subject to the successful completion of a background verification (“BGV”) check conducted by a third-party agency appointed by WSP India.

• Candidates are advised to ensure that all information provided during the recruitment process — including documents uploaded — is accurate and complete, both to WSP India and its BGV partner”.