AI Engineer – Generative AI

About the role

WSP is seeking an AI Engineer to develop, deploy, and support production-oriented Generative AI solutions for its Middle East AI portfolio from the Bengaluru Global Capability Centre (GCC). The role focuses on building AI applications, intelligent agents, automation workflows, and enterprise integrations using Microsoft Azure's approved AI technology stack. The successful candidate will implement retrieval-augmented generation (RAG), prompt engineering, embeddings, function calling, and structured outputs. Responsibilities include building data ingestion and retrieval pipelines, integrating enterprise APIs, evaluating AI solution quality, implementing responsible AI safeguards, and supporting deployment, monitoring, troubleshooting, and continuous improvement. The position offers an opportunity to work with globally distributed teams and contribute to secure, scalable, and maintainable enterprise AI solutions.

What you bring

- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field. - 0–3 years of relevant software, data, or AI engineering experience, including internships or strong project experience. - Working knowledge of Python, REST APIs, SQL, and software engineering fundamentals. - Practical understanding of LLMs, embeddings, RAG, prompt engineering, and AI evaluation. - Exposure to Microsoft Azure AI services and cloud security principles. - Familiarity with Git, CI/CD, automated testing, and collaborative development. - Strong analytical, debugging, documentation, and communication skills. - Ability to collaborate with product owners, engineering teams, and international stakeholders. - Willingness to comply with WSP's background verification process.

What we offer

- Hybrid working model. - Opportunities to work on international AI projects. - Professional development and learning opportunities. - Collaboration with global technology and engineering teams. - Inclusive and diverse working environment. - Employee health, safety, and well-being initiatives. - Exposure to enterprise-grade AI architecture, cloud platforms, and responsible AI practices.

Key skills