AI Innovation Intern

Perspective Therapeutics•Seattle, WA

2d•$21 - $24•Onsite

About The Position

The AI Innovation Intern supports the responsible, practical, and effective use of artificial intelligence across Perspective Therapeutics. This six-month, full-time, onsite internship is intended for current students and recent graduates seeking hands-on experience building and applying AI solutions in a biotechnology environment. The intern will help design and develop internal AI-enabled tools and workflows, prepare training and enablement materials, test emerging AI capabilities, and help teams identify opportunities to apply AI to their work. The role involves collaborating with technical and non-technical colleagues to prototype solutions, gather feedback, communicate limitations, and establish thoughtful AI practices, including careful handling of sensitive data and critical evaluation of AI-generated output. The intern will work with teams across the organization to understand business needs, translate requests into practical solutions, evaluate AI use cases, and support adoption through documentation, demonstrations, and training. The position is based primarily onsite at Perspective Therapeutics' Seattle, Washington headquarters and is temporary, with an expected duration of six months.

Requirements

Currently pursuing or recently completed a degree in computer science, engineering, biostatistics, data science, or another technical or technology-focused business field.
Experience using Claude Code, Cursor, or a similar AI coding tool to build and deliver at least one working project beyond guided tutorials.
Experience building an application, tool, automation, or technical project used by others, and ability to explain key design and implementation decisions.
Practical programming ability in Python and/or JavaScript/TypeScript, including experience calling APIs and working with imperfect or unstructured real-world data.
Ability to use AI coding tools to build, debug, test, and improve working solutions rather than relying solely on tutorials or unvalidated generated code.
Ability to learn how non-technical teams work, ask effective questions, and translate vague requests into defined, appropriately scoped solutions.
Comfort with rapid prototyping and iterative development, including gathering user feedback and refining solutions.
Understanding of common large language model limitations and failure modes, with a skeptical and methodical approach to testing AI capabilities.
Clear verbal and written communication skills, including explaining technical concepts, limitations, and instructions to non-technical audiences.
Curiosity, adaptability, initiative, and willingness to learn unfamiliar business processes and subject matter.
Ability to work independently, manage priorities, seek guidance when appropriate, and follow through on commitments.
Ability to collaborate with colleagues outside engineering and adapt communication to different functions and levels of technical familiarity.
Sound judgment and discretion when handling confidential, sensitive, proprietary, research, clinical, employee, or business information.
Ability to perform the essential duties satisfactorily; reasonable accommodation may be made to enable individuals with disabilities to perform essential functions.

Nice To Haves

Coursework or practical experience in programming and data structures; exposure to databases, machine learning, or software development practices.
Experience working with a client, internal team, consulting group, student organization, or freelance project to understand a problem and deliver a technical solution.
Interest in biotechnology, clinical research, healthcare, or life sciences data.
Built a working application, tool, or automation used by others and can explain the problem, technical choices, trade-offs, and results.
Collaborated with business, operations, research, clinical, or other non-engineering partners and adapted technical communication for them.
Taken ownership of a project with unclear scope and determined what to build without step-by-step direction.
Participated in a consulting internship, student consulting group, capstone, research project, freelance engagement, or similar experience involving a real stakeholder.
Experience preparing user documentation, delivering demonstrations, conducting training, or supporting adoption of a new tool.
Curiosity about biotechnology, clinical research, healthcare data, and responsible AI use in a regulated environment.

Responsibilities

Design, build, and improve internal AI tools, automations, and workflows that address business needs.
Use AI-assisted coding tools such as Claude Code, Cursor, or similar platforms to develop prototypes and, as appropriate, production-ready solutions.
Write and maintain code in Python, JavaScript, and/or TypeScript; connect to APIs; and work with spreadsheets, PDFs, documents, and exported data.
Create rapid prototypes, gather user feedback, and iterate based on usability, reliability, and business value.
Document solution requirements, design choices, dependencies, testing results, known limitations, and recommended next steps.
Meet with teams across the organization to understand how work is performed, identify pain points, and assess where AI may provide meaningful support.
Translate broad or ambiguous requests into scoped problems, requirements, and buildable solutions.
Assess AI use cases based on feasibility, expected value, risk, data sensitivity, maintainability, and user readiness.
Collaborate with business, operations, research, clinical, and other functional partners, adapting communication to each audience.
Test new AI tools, models, and capabilities using defined scenarios and representative inputs.
Evaluate AI-generated output for accuracy, consistency, completeness, usability, and common language-model failure modes, including fabricated or unsupported information.
Identify risks, edge cases, and performance limitations; communicate findings and recommend controls or human review.
Follow company policies and applicable requirements for privacy, information security, confidential information, and responsible AI use.
Exercise judgment when handling sensitive business, employee, research, clinical, or healthcare-related information.
Prepare user guides, job aids, demonstrations, and training materials for non-technical audiences.
Explain AI-enabled tools, their limitations, and how users should review or validate their output.
Support demonstrations, office hours, pilot activities, feedback sessions, and other adoption efforts.
Share lessons learned, reusable approaches, and effective practices for responsible AI use.