Software Engineering Intern – AI Enablement

Job Summary: 

The Software Engineering Intern – AI Enablement supports the design and delivery of AI-enabled tools and automation that improve internal productivity and adoption of AI capabilities. The intern will work under the guidance of senior engineers to help build a single view of AI adoption and ROI across tools, improve the usability and installation experience of internal AI developer resources, and automate repeatable AI-related tasks into reliable scheduled jobs. The role partners with technical and business stakeholders to deliver secure, scalable solutions.

Key Responsibilities:

Foundational Programming Skills 

• Assist with building and enhancing internal software tools that support AI enablement initiatives, under senior guidance. 
• Write, test, and debug code for well-defined features and automation tasks. 
• Apply object-oriented programming fundamentals and software design patterns as part of day-to-day development work. 

Cloud & SaaS Awareness 

• Support cloud-based development activities related to internal AI tooling and reporting (e.g., services, scripts, or integrations). 
• Gain exposure to CI/CD and basic deployment concepts for internal tools (build, release, versioning, environment awareness). 
• Contribute to automation work such as migrating manual tasks into scheduled jobs where applicable. 

Healthcare Compliance Knowledge 

• Follow secure coding practices and team standards, including responsible handling of data and access as required by the team’s environment. 
• Build awareness of healthcare privacy concepts and interoperability standards as relevant to the systems and workflows your tooling may touch. 

AI Readiness & Data Literacy 

• Contribute to initiatives that track and improve AI usage, including helping build a single view of AI adoption and ROI across tools. 
• Support the improvement of internal AI enablement assets (e.g., expanding an AI developer repository into a more turnkey installation/adoption experience). 
• Develop familiarity with AI/ML concepts and how AI-enabled solutions are embedded into real workflows (prototyping and scaling concepts as exposure allows).

Collaboration & Communication

• Collaborate with engineers and partners to understand requirements and deliver working solutions incrementally. 
• Participate in agile team routines (standups, planning, demos) and communicate progress, risks, and learnings. 
• Contributes to documentation and enablement artifacts (how-to notes, setup steps, basic runbooks) to help others adopt and sustain solutions.

Required Qualifications:

Education & Experience

• Currently pursuing a Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field. Graduating December 2026 or later. 
• Internship, academic, or project experience in software development (coursework, capstone, research, or personal projects). 
• Interest in AI enablement, automation, developer tooling, or analytics/measurement (adoption, usage, ROI) is strongly preferred.

Other Preferred Knowledge, Skills, Abilities or Certifications: 

• Programming Languages: Python, JavaScript, or Java (TypeScript a plus). 
• Cloud Platform Exposure: Familiarity with AWS or Azure; exposure via labs/projects acceptable. 
• Version Control & Collaboration Tools: Git/GitHub; familiarity with Jira or similar tools. 
• Automation & Scheduling Concepts: Comfort building repeatable scripts or automations; interest in turning manual tasks into scheduled jobs. 
• Documentation/Enablement Mindset: Ability to write clear setup steps or lightweight guides that help others adopt tools. 
• AI Awareness: Exposure to AI/ML fundamentals and/or interest in practical LLM/automation use cases (not required, but helpful).