Digital & AI Engineer – GHG emissions MMT Support

Quest Global; Bengaluru; Hybrid; INR 900,000 - 1,300,000; Full time

Job summary

Quest Global seeks to advance a hybrid role blending engineering insight with AI-driven workflows for GHG emissions booklet reports. You will map end-to-end processes, create AI-ready instructions, and establish traceability and quality checks.

The work combines technical assessment, data synthesis and governance to deliver draft reports for review. The role emphasizes collaboration with SMEs, development of a prompt library, and scalable automation while ensuring confidentiality and

Qualifications

• Degree in process, chemical, mechanical, energy or equivalent engineering.
• Experience in technology assessment, engineering studies, R&D or technical reporting.
• Ability to critically review technical literature, supplier information and techno-economic data.
• Practical experience with generative AI, prompt engineering and multi-document synthesis.
• Familiarity with Microsoft 365, SharePoint and preferably Copilot Studio, Power Automate or Python.
• Strong technical writing, structuring and communication skills in English.
• Ability to work with subject-matter experts and translate engineering practices into repeatable workflows.
• Recommended experience: 5 to 10 years, with a combination of industrial engineering and applied digital or AI experience.

Responsibilities

• Review the existing GHG emissions EVALUATE methodology, booklet report template, and example reports previously issued.
• Map the end-to-end process from source-document collection to booklet report drafting.
• Convert the standard booklet report structure into AI-ready instructions, prompts and templates.
• Develop workflows for technical information extraction and synthesis, KPI and cost-data structuring, supplier and project landscape review, identification of data gaps or conflicting information, and drafting and quality checking of booklet report sections.
• Implement source traceability, confidentiality controls and clear distinction between supplier claims, confirmed data, assumptions and engineering judgement.
• Define technical and editorial quality checks, with human validation gates.
• Pilot the method on selected GHG emissions technologies and improve it based on feedback.
• Produce a user guide, prompt library and recommendations for further automation.

Skills

Technology assessment

Prompt engineering

AI multi-document synthesis

Technical writing

English communication

Cross-functional collaboration

Education

Engineering degree (process/chemical/mechanical/energy)

Tools

Microsoft 365

SharePoint

Copilot Studio

Power Automate

Python

Job description

Job RequirementsAt Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster.

Job RequirementsAt Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster. Support GHG emissions in designing and piloting a repeatable, reliable and traceable AI-assisted process for generating Technology EVALUATE Booklet Reports. The role requires a hybrid profile combining engineering understanding, technology assessment and practical generative-AI skills. The engineer will focus primarily on developing the AI-assisted drafting method and workflow, while GHG emissions Technology Champions remain accountable for checking the overall consistency and final approval.

Main Responsibilities

• Review the existing GHG emissions EVALUATE methodology, booklet report template, and example reports previously issued.
• Map the end-to-end process from source-document collection to booklet report drafting.
• Convert the standard booklet report structure into AI-ready instructions, prompts and templates.
• Develop workflows for technical information extraction and synthesis, KPI and cost-data structuring, supplier and project landscape review, identification of data gaps or conflicting information, and drafting and quality checking of booklet report sections.
• Implement source traceability, confidentiality controls and clear distinction between supplier claims, confirmed data, assumptions and engineering judgement.
• Define technical and editorial quality checks, with human validation gates.
• Pilot the method on selected GHG emissions technologies and improve it based on feedback.
• Produce a user guide, prompt library and recommendations for further automation.

Expected Deliverables

• Target AI-assisted booklet-generation workflow.
• AI-ready booklet specification and prompt library.
• Source-traceability and quality-control framework.
• One or several pilot Technology EVALUATE Booklet reports, to be defined.
• User guide and recommendations for scaling the process.

Key Success Criterion

• A new technology booklet report can be initiated from a defined set of source documents using a documented workflow and issued for review (draft level).
• Each major factual claim and numerical value can be traced to a source or explicitly identified as an assumption or engineering judgement.
• The booklet report generated at draft level follows the mandatory GHG emissions structure and terminology.
• The process clearly identifies missing, contradictory or low-confidence information.
• The Technology Champion can efficiently review, correct and approve the AI-generated draft.
• The method is reusable across different decarbonization technologies.
• The solution respects information-access and confidentiality constraints.
• GHG emissions retain full human control of technical conclusions and governance decisions.

We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.

We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.

Work Experience

Profile Required

• Degree in process, chemical, mechanical, energy or equivalent engineering.
• Experience in technology assessment, engineering studies, R&D or technical reporting.
• Ability to critically review technical literature, supplier information and techno-economic data.
• Practical experience with generative AI, prompt engineering and multi-document synthesis.
• Familiarity with Microsoft 365, SharePoint and preferably Copilot Studio, Power Automate or Python.
• Strong technical writing, structuring and communication skills in English.
• Ability to work with subject-matter experts and translate individual GHG emissions lead technologist engineering practices into repeatable workflows.
• Recommended experience: 5 to 10 years, with a combination of industrial engineering and applied digital or AI experience.