Solutions Engineering Intern - Commerical Team (Chicago)

About the role

Salt AI is looking for a motivated intern to work directly with our Chief Business Officer and Sales Solutions team. You’ll help design, prototype, and implement AI-driven solutions across pharmaceutical, biotech, and enterprise applications—with hands-on exposure to how agentic AI can transform real-world R&D and commercial workflows. You’ll work directly with the Salt toolkit alongside experienced scientists, engineers, and forward-deployed solutions experts.

Responsibilities

• Architect and iterate on agent-based systems that execute complex workflows, particularly in drug discovery and life sciences R&D.
• Work alongside the CBO and solutions engineers to understand client workflows end-to-end, from initial discovery through prototype delivery.
• Build functional workflow prototypes using Salt’s orchestration platform, translating client and research problems into working demonstrations.
• Reproduce and evaluate existing AI models and research papers to assess their applicability within Salt’s infrastructure.
• Help identify opportunities within drug discovery and adjacent domains where AI can meaningfully enhance processes and outcomes.
• Support the development and optimization of ML and deep learning models for research applications, adapting them for new use cases.
• Research domain-specific requirements across life sciences, financial services, and energy—feeding findings back to the commercial and product teams.
• Contribute to reusable templates, documentation, and technical content that enable partners to self-serve and scale.
• Stay current with emerging AI trends, agent frameworks, and orchestration tooling, and share insights with the broader team.
• Collaborate cross-functionally to translate scientific and business problems into AI-driven approaches.

Requirements

• Currently pursuing a Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Data Science, Bioinformatics, Computational Biology, or a related field.
• Experience with LLMs, agent frameworks, or workflow orchestration tools (e.g., LangChain, AutoGen, BioNemo, or similar).
• Familiarity with AI-assisted coding tools (e.g., Claude Code, Codex, or similar).
• Academic or personal AI/ML project experience—you’ve built things, not just studied them.
• Exposure to analyzing or reproducing research papers.
• Coursework or project work related to life sciences, bioinformatics, or computational biology.
• Strong analytical and problem-solving skills.
• Effective communication and teamwork skills—able to translate technical concepts into practical, client-facing applications.
• Willingness to learn and adapt in a fast-paced, build-from-scratch environment.

Nice to have

• Prior experience in drug discovery or AI research.
• Interest in pharmaceutical or biotech applications, particularly therapeutic discovery pipelines.
• Familiarity with scientific computing environments, data lineage, or provenance tracking.
• A scrappy mentality—comfortable wearing multiple hats, driving clarity in ambiguous situations, and doing whatever it takes to move things forward.

Perks and Benefits

• Competitive internship compensation based on location.
• Fully remote environment, working primarily within U.S.-based time zones.
• Direct mentorship from senior leadership including the CBO and solutions engineering team.