This position is responsible for contributing to the design, delivery, and support of production-grade artificial intelligence systems under close guidance. This role applies foundational software engineering, data management, and generative AI skills to implement well-defined components of AI-powered applications and automated workflows. The Artificial Intelligence Engineer I focuses on building strong SQL and data management capabilities, learning enterprise AI standards, and developing proficiency in production software practices.
Responsibilities:
Implements well-defined components of AI solutions, including LLM-based application features and supporting services, under guidance.
Develops and maintains Python-based scripts, APIs, and services that support AI workflows and integrations.
Writes, optimizes, and validates SQL queries and data transformations used by AI systems; supports data quality checks and basic troubleshooting.
Assists with retrieval-augmented generation (RAG) components such as document ingestion, indexing, retrieval configuration, and prompt assembly.
Supports creation of evaluation datasets and execution of basic evaluation procedures to measure model outputs and system quality.
Follows established testing, documentation, security, and deployment practices to ensure production readiness for assigned work.
Identifies data issues, model failure modes, or operational risks and escalates concerns appropriately.
Qualifications:
Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field, or equivalent demonstrated practical experience.
Zero to two (0-2) years or equivalent demonstrated experience in software engineering, data engineering, analytics engineering, or AI-related development.
Proficiency in SQL and foundational data management skills, including data validation, data quality awareness, and working with structured datasets (core requirement).
Proficiency in Python for application development, scripting, and basic API integration.
Introductory experience with generative AI application development, including prompt-based workflows and model-assisted features.
Familiarity with Git and modern development practices (branching, code review, and issue tracking).
Exposure to LLM tooling such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar is beneficial but not required.
Ability to communicate clearly, ask good questions, and incorporate feedback through iterative development.
This job specification should not be construed to imply that these requirements are the exclusive standards of the position. Incumbent will follow any other instructions, and perform any other related duties, as may be required by the supervisor.
