
Senior Engineer–AI Sustainable building design
Wsp · Noida, Uttar Pradesh, India · Bengaluru, Karnataka, India
- Professional Services
- 10,001+ employees
- Montreal, Quebec
Mixed hiring record · median 48 days open
All reasons
- Open 118 days
- 35% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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”.
Skills
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