AI Engineer

Company Description
D Globalist (DG) is a global expansion ecosystem and platform designed for ventures with international potential, supporting growth across more than 160 countries. DG helps founders move from intent to execution by enabling market entry, regulatory navigation, client acquisition, capital access, and strategic partnerships. The company is focused on building a new category of founders called eXtrepreneurs—entrepreneurs who design for global markets from day one. Through eXtrefy, DG’s founder network and expansion platform, the organization drives cross-border growth via trusted connections and collaborative opportunities.
Role Description
As an AI Engineer at D Globalist, you will design, develop, and deploy AI models and systems that power DG’s global expansion platforms and tools. You will work closely with product, engineering, and business teams to translate complex business challenges into scalable AI solutions, including applications in natural language processing and pattern recognition. Daily responsibilities include building and optimizing neural network architectures, writing production-grade software, integrating AI components into existing systems, and testing and monitoring performance. You will also research emerging AI techniques, evaluate new tools and frameworks, and contribute to technical documentation and best practices. This is a full-time, on-site role based in New Delhi.
What you’ll work on
Integrating AI models and third-party APIs into the application
Creating, testing and refining prompts for founder matching, recommendations and personalised insights
Translating business requirements into AI workflows and scoring logic
Managing data workflows to improve the quality and relevance of AI outputs
Working with the development team to launch features and improve accuracy, speed and reliability
What we’re looking for
1–5 years of relevant experience in AI/ML or software engineering
Strong Python skills and practical experience with LLM APIs
Experience with prompt engineering, structured outputs and API integrations
Ability to evaluate AI outputs and turn feedback into product improvements
A hands-on approach and the ability to own implementation alongside the product and technology teams
Experience with RAG, vector databases or recommendation engines would be a plus.
We’re particularly interested in candidates who have shipped AI features into live products.

Work arrangement
No