Software Engineer, AI Engineering Workflows

Responsibilities

• Design, build, and maintain AI-assisted developer productivity tools, code quality automation, and modern CI/CD infrastructure.
• Translate software development requirements into clear software designs, internal developer APIs, and repository templates.
• Lead technical design discussions and establish safe, practical standards for using AI-generated code and agentic tools across the department.
• Proactively address code quality, testing, and reliability gaps by building robust automated testing frameworks and code-review gating systems.
• Write clear runbooks, documentation, and training guides to help engineering teams adopt AI-assisted development tools responsibly.
• Collaborate with other software teams to systematically debug complex issues across system boundaries and ensure safe release processes.

Requirements

• An independent software engineer who can own a distinct system, feature, or service from design to production.
• Hands‑on experience using AI‑assisted development tools and writing software automation or integrations.
• Experience in software quality practices, automated testing, code review, and modern CI/CD pipelines.
• Write clean, readable, and documented code that follows established engineering patterns.
• Proficiency in modern programming languages (such as Python, C++) and web service development.
• Solid understanding of software architecture, APIs, repository structure, and CI/CD automation.
• Communicate complex technical concepts in simple, clear language to both technical and non‑technical partners.
• Effective in ambiguous or changing priority environments and translate loose needs into structured software plans.
• High curiosity and an active growth mindset to learn new technical domains.
• Provide constructive, detailed feedback in code reviews and mentor other engineers on tooling and best practices.
• Preferred: experience building developer experience platforms, internal tools, repository templates, or custom engineering infrastructure.
• Preferred: experience with agentic coding frameworks, prompt engineering, or LLM‑based development APIs.
• Preferred: experience in high‑complexity engineering environments where software closely interacts with hardware or scientific instruments.