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 teams 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 Bachelors 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).