AI Engineer II

Software Engineer II designs, develops, tests, and debugs software applications, contributes to software builds, completes code reviews and automated testing to maintain high-quality standards with guidance, supports and monitors software across environments, and adheres to security and regulatory best practices. Designs, develops, tests, and debugs software applications and systems, including AI/GenAI-powered applications and intelligent automation solutions. Develops and integrates Generative AI capabilities using Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and vector databases where applicable. Completes software builds through consistent development practices, including the use of tools, common components, AI frameworks, and documentation with guidance from peers and leaders. Completes code reviews and automated testing to maintain high-quality code standards, including evaluation and validation of AI model outputs, with guidance from peers and leaders. Supports and monitors software across test, integration, and production environments, including monitoring AI application performance, quality, and reliability. Adheres to security, responsible AI, and regulatory best practices to ensure software and AI solution compliance. Collaborates and co-creates effectively with teams in product and the business to align technology initiatives and AI-driven solutions with business objectives. Education Qualifications: Bachelor’s degree in Computer Science, Computer Engineering, and/or comparable experience. Knowledge of distributed (multi-tiered) systems, algorithms, NoSQL and relational databases. Knowledge of the core tools used in the planning, analyzing, crafting, building, testing, configuring, and maintaining of assigned application(s). Familiarity with Generative AI concepts, Large Language Models (LLMs), prompt engineering, embeddings, vector databases, Retrieval-Augmented Generation (RAG), AI orchestration frameworks (e.g., LangChain/LlamaIndex), and cloud AI services is preferred. Work Experience: Software engineering and development experience or a related job. Experience in application design, software development, and automated testing. Experience in object-oriented design and coding with a variety of programming languages. Experience in distributed (multi-tiered) systems, algorithms, and relational databases. Experience in Agile software development methodologies and practices such as Scrum/Kanban, iterations, and user stories. Experience in automation testing and documentation (i.e. automated, functional, and performance). Experience building, integrating, or deploying AI/GenAI solutions using LLM APIs, AI frameworks, cloud AI platforms (e.g., Azure OpenAI, AWS Bedrock, Google Vertex AI), or open-source models is preferred. Exposure to prompt engineering, RAG pipelines, vector databases, AI evaluation techniques, and model observability is a plus.