Associate Software Engineer, AI Solutions

About the Role

Cayuse is seeking an Associate Software Engineer, AI Solutions, to join their remote-first team. This entry-level role focuses on building AI capabilities directly into Cayuse products, working alongside senior engineers. The position is 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.

Key Responsibilities

• AI Agent Development: Build and maintain AI agents that use large language models to complete multi-step tasks within Cayuse products.
• MCP Server Development: Help build and extend Model Context Protocol (MCP) servers for secure AI assistant interaction with Cayuse products.
• Hybrid AI Validation: Turn AI-extracted rules into deterministic, auditable validations.
• Product Integration: Integrate AI features into existing Cayuse applications through platform APIs.
• Testing & Evaluation: Write unit and integration tests for AI features, and help build evaluation sets to measure AI output metrics.
• Deployment & Operations: Ship code through CI/CD pipelines to cloud environments (AWS, including Amazon Bedrock).
• Learning & Collaboration: Participate in code reviews, design discussions, and sprint ceremonies.
• Governed AI Platform: Develop AI features using Cayuse's shared AI platform and established engineering standards.
• Responsible AI & Security: Follow security and privacy standards when developing AI features.

Requirements & Tech Stack

• Software Development: Proficient in at least one general-purpose language (Python or TypeScript/JavaScript preferred; Java with Spring Boot also valued).
• AI & LLM Fundamentals: Demonstrated interest in AI technologies. Experience experimenting with LLM APIs, prompt engineering, tool calling, or retrieval-augmented generation (RAG) is a plus.
• Agents & MCP: Familiarity with the Model Context Protocol, agent frameworks, or AI coding assistants.
• APIs & Integration: Working understanding of REST APIs, JSON, and authentication basics.
• Cloud & Infrastructure: Exposure to a cloud platform (AWS preferred; Amazon Bedrock a plus), containers (Docker), or CI/CD pipelines is a plus.
• Data Fluency: Comfortable writing basic SQL queries and working with structured data. Exposure to Snowflake or another cloud data warehouse is a plus.
• Version Control: Exposure to team-based development using Git.
• Agile Practices: Exposure to agile practices.

Qualifications

• 0–2 years of professional software development experience, including internships, co-ops, or apprenticeships.
• Demonstrated ability to build working software through coursework, internships, personal projects, open-source contributions, or hackathons. A portfolio or GitHub profile is strongly encouraged.
• BS in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
• Clear communicator — writes readable code, documentation, and pull request descriptions.
• Strong problem-solving instincts.
• Coachable and growth-oriented.
• Collaborative and adaptable.
• Genuine curiosity about how AI is changing software and knowledge work.