Associate Software Engineer, AI Solutions

Role overview Help develop and ship AI-enabled features within software products used by research organizations and their administrators. This early-career engineering role focuses on practical product development with guidance from senior engineers: building agents and integrations, validating AI behavior, and connecting capabilities to existing customer workflows. It is software engineering work rather than machine learning research.

Responsibilities - Build and maintain LLM-powered agents that call tools, retrieve information, and carry out multi-step tasks; implement prompts and orchestration logic with senior guidance. - Extend MCP servers and related APIs, including authentication and permission checks, and provide reusable documentation and tests. - Help convert rules extracted with AI into deterministic, auditable checks that can be reviewed by people. - Integrate AI features into existing applications using shared platform patterns and established APIs. - Write unit and integration tests, help evaluate accuracy, reliability, latency, and cost, and investigate failures. - Deploy through CI/CD to cloud environments, add logging and monitoring, and follow security and privacy practices such as permissions and tenant isolation.

Requirements - 0–2 years of software development experience; internships, co-ops, and apprenticeships count. - A relevant bachelor’s degree or equivalent practical experience, with demonstrated ability to build working software through projects, coursework, or professional experience. - Familiarity with team development practices such as Git, code review, and agile workflows. - Proficiency in at least one general-purpose language; Python or TypeScript/JavaScript are preferred, and Java with Spring Boot is also relevant. - Foundations in data structures, APIs, error handling, and testing, plus basic familiarity with REST, JSON, and authentication. - Clear written and verbal communication, a methodical approach to ambiguous tasks, openness to feedback, and curiosity about practical uses of AI.

Nice to have Experience experimenting with LLM APIs, prompt design, tool calling, or retrieval-augmented generation is useful. Familiarity with MCP, agent frameworks, AI coding assistants, AWS or Bedrock, Docker, CI/CD, SQL, or data warehouses is also valued; specific AI framework experience is not required.

Benefits and work setup Remote-first environment with a flexible schedule. Listed benefits include medical coverage options, employer-paid vision, dental, and short-term disability coverage, paid time off and holidays, a remote work stipend, paid parental leave, 401(k) matching, and a quarterly wellness reimbursement.