Associate AI Engineer

Associate AI Engineer

The Associate Applied AI Engineer supports the development, deployment, and maintenance of artificial intelligence applications for the Columbia University Irving Medical Center (CUIMC). This role contributes to the design and implementation of AI-enabled solutions that support administrative, research, clinical, and educational operations across the institution.

Working closely with senior engineers and cross-functional teams, the Junior Engineer assists in building applications that leverage large language models (LLMs), retrieval-augmented generation (RAG), automation frameworks, and machine learning techniques. This role focuses on implementing AI solutions, supporting application deployment, and ensuring systems operate securely, efficiently, and in alignment with institutional policies and governance standards.

Responsibilities

Essential Duties:

• Design, develop, and maintain AI-enabled applications utilizing retrieval-augmented generation (RAG) techniques to enhance knowledge discovery, automate workflows, and support decision-making across CUIMC operations.
• Build scalable AI tools and services that integrate with CUIMC administrative, clinical, research, and educational systems.
• Develop rapid proof-of-concept prototypes to evaluate new technologies and demonstrate solution feasibility to stakeholders.
• Assist with optimization of prompts, pipelines, and model workflows to improve application performance and reliability.

Technical Support and Documentation

• Troubleshoot AI applications and assist with diagnosing and resolving technical or performance issues in development or production environments.
• Maintain clear technical documentation, including architecture diagrams, workflows, and implementation notes to support system sustainability and team knowledge sharing.

Operations & Continuous Improvement

• Monitor emerging developments in artificial intelligence, machine learning frameworks, and generative AI technologies relevant to healthcare and higher education.
• Prototype solutions using open-source tools and AI platforms present demonstrations or findings to internal stakeholders.
• Participate in exploratory initiatives assessing new AI capabilities and their potential institutional impact.

Responsible AI and Compliance

• Support the design and deployment of AI solutions that prioritize privacy, transparency, security, and ethical use of data.
• Adhere to CUIMC policies related to data governance, compliance, and institutional review requirements.
• Contribute to the development of internal best practices and governance frameworks for the safe and responsible use of generative and predictive AI technologies.

People

• Partner with engineers, analysts, data scientists, and institutional stakeholders to design and implement AI-enabled solutions.
• Participate in stakeholder discussions to assess needs and recommend AI tools aligned with institutional priorities.

Other

• Perform other related duties and responsibilities as assigned/requested.

Minimum Qualifications

• Bachelor's degree or equivalent in education and experience, plus four years of experience.

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Statistics, or equivalent combination of education and experience.
• Minimum 4 years of professional experience in software engineering, artificial intelligence, machine learning, data engineering, or a related technical field.
• Experience with at least one programming language commonly used for AI or application development (e.g., Python, JavaScript, TypeScript, Java, or C#).
• Experience developing, testing, and maintaining software applications, data pipelines, or AI-enabled solutions.
• Strong analytical and problem-solving skills with the ability to translate technical concepts into practical solutions.
• Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Statistics, or a related discipline.
• Experience developing applications that leverage large language models (LLMs), generative AI tools, or retrieval-augmented generation (RAG).
• Familiarity with AI development frameworks or orchestration tools such as LangChain, LlamaIndex, or similar technologies.
• Experience deploying applications or machine learning workflows in cloud environments such as AWS, Google Cloud Platform, or Microsoft Azure.
• Exposure to AI platforms such as Amazon Bedrock, Google Vertex AI, or Azure AI Studio.
• Experience working with natural language processing (NLP), data extraction, or analytics involving structured and unstructured data.
• Familiarity with Agile development practices, Git-based version control, and collaborative software development workflows.

Equal Opportunity Employer / Disability / Veteran

Columbia University is committed to the hiring of qualified local residents.