Associate Software Engineer, AI Solutions - Cayuse

About the Role

Join our remote-first culture as an Associate Engineer, an entry-level, hands-on engineering role focused on building AI capabilities directly into Cayuse products. You will work alongside senior engineers to design, build, test, and ship AI agents, Model Context Protocol (MCP) servers, and LLM-powered features that help research institutions work faster and with less manual effort.

This is a software engineering role for someone early in their career who writes solid code, learns quickly, and wants to grow into a strong AI engineer by shipping real features to real customers.

Responsibilities

• AI Agent Development: Build and maintain AI agents using LLMs (e.g., Claude) to complete multi-step tasks, call tools, and retrieve data.
• MCP Server Development: Extend Model Context Protocol servers to allow AI assistants to securely interact with Cayuse products.
• Hybrid AI Validation: Convert AI-extracted rules into deterministic, auditable validations.
• Product Integration: Integrate AI features into existing applications via platform APIs.
• Testing & Evaluation: Write unit/integration tests and build evaluation sets to measure accuracy, reliability, latency, and cost.
• Deployment & Operations: Ship code via CI/CD pipelines to AWS (Amazon Bedrock) and implement logging/monitoring.
• Learning & Collaboration: Participate in code reviews, design discussions, and stay current with the AI ecosystem.
• Governed AI Platform: Develop features using shared standards for security, tenant isolation, and auditing.
• Responsible AI & Security: Test for risks like prompt injection and unauthorized data access.

Qualifications

• Experience: 0–2 years of professional software development experience (internships, co-ops, or apprenticeships).
• Portfolio: Demonstrated ability to build software via coursework, personal projects, or open-source contributions.
• Technical Skills: Proficient in Python or TypeScript/JavaScript (Java/Spring Boot also valued). Solid grasp of data structures, APIs, and testing.
• AI Fundamentals: Interest in LLM APIs, prompt engineering, tool calling, or RAG.
• Collaboration: Strong problem-solving instincts, clear communication, and a growth-oriented mindset.
• Education: BS in Computer Science, Software Engineering, or equivalent practical experience.