Gen Ai Developer

The Job

As a Gen Ai developer, you will designs, develops, and implements scalable AI and Generative AI solutions that improve customer experience, business efficiency, and decision-making.

The role builds production-grade applications and workflows using Python, SQL, large language models, Retrieval-Augmented Generation, and agentic AI frameworks.

It applies advanced analysis, prompt engineering, evaluation, and observability practices to deliver reliable and useful AI capabilities.

• Design, develop, test, and deploy robust AI and Generative AI solutions that improve customer experience, operational efficiency, and business decision-making.
  • Build and deploy production-grade workflows, applications, and data pipelines using Python, SQL, relational databases, and modern AI tools.
  • Perform advanced exploratory analysis and feature engineering across structured and unstructured datasets to support scalable AI and Generative AI use cases.
  • Implement prompt engineering strategies, conduct LLM experiments, and apply output evaluation frameworks to ensure quality, relevance, accuracy, safety, and business usefulness.
  • Develop and scale Retrieval-Augmented Generation pipelines and integrate agentic AI frameworks for multi-step reasoning and workflow automation.
  • Implement AI observability and MLOps practices to monitor model behavior and system reliability; collaborate with cross-functional teams and communicate findings, risks, and recommendations to stakeholders.

Qualifications

Whats needed to succeed (Minimum Qualifications):

Candidates must hold a Master of Science or equivalent postgraduate degree in a STEM field.

• Data Science, Statistics, Engineering, Computer Science, Operations Research, or a related STEM field.

• 1–2 years of industry experience in AI engineering, data science, analytics, or machine learning, including practical experience moving models or analytical workflows toward production.

• Strong Python and SQL proficiency; software engineering fundamentals, including Git; experience with large relational datasets and platforms such as Microsoft SQL Server, Snowflake, BigQuery, or Teradata; practical knowledge of LLMs, prompt engineering, embeddings, RAG, and agentic AI; AI observability and MLOps; strong analytical problem-solving; ability to create clear Excel and PowerPoint presentations