Description
WSP is seeking an AI Engineer to develop and support production-oriented Generative AI solutions for the Middle East AI portfolio from the Bengaluru GCC.
Responsibilities
- Develop GenAI applications, agents and automation workflows using approved designs and engineering standards.
- Implement retrieval-augmented generation, function calling, structured outputs and prompt patterns to improve solution reliability and usability.
- Integrate AI components with enterprise systems, APIs, approved vector search services and governed data sources.
- Build and maintain ingestion, chunking, embedding, indexing and retrieval pipelines for structured and unstructured content.
- Create evaluation datasets and execute repeatable testing for accuracy, grounding, safety, latency and solution quality.
- Apply responsible AI controls including validation, guardrails, content filtering, traceability and human oversight.
- Develop clean, reusable and well-documented Python components and participate in code reviews.
- Support deployment, monitoring, incident resolution and continuous optimisation of AI solutions.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Data Science or a related discipline.
- 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 evaluation methods.
- Exposure to Azure AI services, Git-based development, CI/CD and cloud security principles.
- Strong analytical, troubleshooting, documentation and stakeholder communication skills.
Expected Outcomes
- Deliver maintainable AI components that progress from prototype through controlled production deployment.
- Improve solution quality through structured evaluation, monitoring and iterative optimisation.
- Contribute to reusable AI capabilities and patterns across the Middle East portfolio.
Preferred Qualifications
- Microsoft Azure or Azure AI certification.
- Experience with agentic AI orchestration, document intelligence or enterprise search.
- Knowledge of MLOps, model lifecycle management and production monitoring.
- Experience working in multi-disciplinary, agile or globally distributed teams.