AI Engineer

This is an early IT career, hands-on role designed for candidates who want to build a strong foundation in Artificial Intelligence and Generative AI systems. You will contribute to real-world AI solutions-such as retrieval-based applications, internal copilots, and workflow automation-while learning enterprise-grade engineering practices in a regulated financial services environment.

What You’ll Do Assist in building and enhancing Generative AI applications such as RAG-based solutions, internal copilots, and AI-powered workflows. Contribute to prompt development, testing, and basic evaluation of LLM outputs. Support implementation of data ingestion, chunking, embeddings, and retrieval pipelines. Write and maintain clean, well-tested code using Python. Work with cloud-native services (Azure and/or AWS). Participate in CI/CD pipelines and automated testing. Learn and follow Responsible AI, security, and compliance guidelines. Collaborate with cross-functional teams to understand business use cases. Document implementations and contribute to knowledge sharing. Stay current with emerging GenAI tools and practices.

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI/ML, or a related field. 0-5 years of experience in software development, data engineering, or AI/ML (internships count). Foundational understanding of AI and machine learning concepts. Exposure to Generative AI concepts such as LLMs, embeddings, or retrieval-based systems. Hands-on experience with Python. Familiarity with cloud concepts (Azure or AWS). Knowledge of Git and software development workflows. Strong problem-solving skills and eagerness to learn. Good communication and teamwork skills.

Nice to Have Projects involving chatbots, LLMs, or GenAI applications. Exposure to Azure OpenAI, OpenAI APIs, Hugging Face, LangChain, or vector databases. Basic knowledge of DevOps or MLOps concepts. Familiarity with information retrieval or search. Exposure to financial services or regulated industries.

What Will Really Catch Our Eye Personal or academic AI/GenAI projects. Demonstrated ability to learn new tools quickly. Clear documentation or presentations of technical work. Evidence of collaboration or peer mentoring. Passion for solving real-world business problems with technology.