[Remote] Principal AI-Native Software Engineer

Note: The job is a remote job and is open to candidates in USA. ButterflyMX develops smartphone-based access control products that help people open and manage doors and gates. The Principal AI-Native Software Engineer will independently take product initiatives from business requirements through secure, tested, production-ready delivery using Claude Code and multiple AI agents. The role owns architecture, implementation, deployment, infrastructure, operational improvement, and collaboration with Product and Design across the company’s software stack.

Responsibilities

• Work closely with Product to understand business requirements, intended user outcomes, priorities, constraints, and acceptance criteria
• Translate Product's business requirements into clear technical requirements, implementation plans, system behaviors, and engineering tasks
• Identify technical ambiguities, dependencies, risks, edge cases, and tradeoffs that must be resolved before or during implementation
• Ask the questions necessary to ensure the engineering solution addresses the actual product need
• Partner with Design to understand intended user workflows and translate designs into complete, functional product experiences
• Provide Product and Design with clear feedback when requirements or designs introduce unnecessary complexity, technical risk, security concerns, or operational challenges
• Preserve the intent of the product requirements while making sound technical and implementation decisions
• Communicate progress, tradeoffs, risks, and changes in scope clearly throughout development
• Take approved product initiatives from business requirements through technical design, implementation, deployment, and ongoing operation
• Manage several products or major engineering initiatives with limited day-to-day oversight
• Develop complete technical requirements from the business and product requirements supplied by Product
• Make thoughtful architectural, implementation, security, infrastructure, and operational tradeoffs within an established platform direction
• Design, build, and maintain efficient, reusable, reliable, and testable code; identify bottlenecks and bugs, devise solutions, and propose optimizations
• Deliver working software quickly while maintaining high standards for reliability, maintainability, security, and user experience
• Own the technical execution of a product rather than waiting for every implementation detail to be specified
• Continue improving products after launch based on feedback, usage, defects, and changing requirements
• Use Claude Code as a primary development environment and orchestration layer
• Run multiple agents, sub-agents, worktrees, branches, or development sessions in parallel
• Decompose technical requirements into work that can be executed safely and effectively by different agents
• Design reusable Claude Code skills, commands, hooks, context files, agent instructions, and development workflows
• Provide agents with the technical requirements, architectural context, constraints, designs, examples, and verification methods necessary to produce high-quality work
• Build feedback loops in which agents review, test, critique, and improve one another's output
• Use agents to investigate unfamiliar systems, understand legacy code, create implementation plans, write code, generate tests, review changes, prepare pull requests, and assist with releases
• Continuously improve the systems, instructions, and tooling that make your own AI-assisted development more reliable and scalable
• Help automate the engineering portions of the product development lifecycle, including:
• Translating business requirements into technical requirements
• Technical discovery and architecture
• Implementation planning
• Design and UX implementation
• Software development
• Automated testing
• Security analysis
• Code review
• Pull-request creation and iteration
• Infrastructure provisioning
• Deployment
• Monitoring and operational support
• Documentation and maintenance
• Create workflows in which agents can execute substantial portions of the development lifecycle while preserving appropriate human judgment and control
• Establish clear quality gates so that agent-generated work is verified rather than accepted on faith
• Develop methods for measuring the effectiveness, quality, cost, and speed of AI-native engineering workflows
• Reduce the manual coordination and repetitive work required to move from an approved product requirement to deployed software
• Review agent-generated code with the judgment expected of a Principal or Staff engineer
• Reject unnecessary complexity, excessive abstraction, inappropriate frameworks, duplicated logic, and changes that are much larger than the problem requires
• Prefer focused, understandable solutions: for example, an eight-file targeted change rather than an eighty-file rewrite when both accomplish the same result
• Ensure software is appropriately tested, observable, secure, maintainable, and production-ready
• Understand how systems work beneath the abstraction layer rather than treating AI output as a black box
• Debug complex issues across application code, infrastructure, data systems, third-party services, and development tooling
• Know when the AI is wrong, when its proposed approach is risky, and when direct engineering intervention is necessary
• Ensure implementations satisfy the agreed product requirements and acceptance criteria without adding unnecessary scope
• Bring deep, hands-on expertise in our core stack — Ruby on Rails, production TypeScript/Node.js, MongoDB and relational data, and cloud infrastructure across AWS and GCP
• Use Claude Code to move confidently into adjacent or unfamiliar codebases — Android, iOS, Go, and others — developing enough understanding to make sound architectural and implementation decisions without waiting for a specialist
• Work across frontend, backend, mobile, infrastructure, integrations, and internal tooling as needed
• Manage infrastructure and deployment workflows across AWS and GCP
• Improve legacy systems rather than avoiding them or insisting that everything be rewritten

Skills

• Significant experience operating at the Staff, Principal, or equivalent engineering level, with 8+ years of professional software development experience
• A track record of independently delivering complex, production software in partnership with Product and Design teams
• Expert-level experience with Claude Code. This is a mandatory requirement. You must be able to demonstrate substantial product development with Claude Code — not merely autocomplete, isolated code generation, or simple prompting
• Experience coordinating multiple AI agents or development sessions in parallel, with a deep understanding of agent context, skills, sub-agents, tool use, planning, verification, and orchestration
• Production experience with both a dynamic language ecosystem and a strongly-typed one. Production TypeScript/Node.js experience is required
• Experience with relational databases (PostgreSQL, MySQL) and document/NoSQL databases. MongoDB experience is required
• Hands-on experience deploying and operating production software in a distributed, cloud-based environment (e.g., AWS EC2/ECS, Lambda, Cloud Run) within a service-oriented or micro-service architecture, across AWS, GCP, or both
• Hands-on experience applying AI/ML in production. For example integrating LLMs or other models into products or workflows, building retrieval or agentic systems, prompt/eval design, or on-device/edge inference
• Extensive experience developing and maintaining APIs and integrating with third-party APIs
• Strong experience with automated CI/CD pipelines and a deep understanding of testing what, when, and how to test
• Strong ability to translate business and product requirements into technical requirements and implementation plans
• Strong product judgment, including the ability to understand user intent, identify edge cases, and recognize when an implementation does not satisfy the underlying requirement
• Strong understanding of software design, architecture, security, reliability, scalability, and maintainability
• Ability to review AI-generated code critically and distinguish high-quality engineering from superficially functional output
• Comfort working across unfamiliar programming languages, frameworks, and legacy systems, using AI to accelerate that work
• Strong ownership, initiative, and bias toward building
• Excellent written and verbal communication, particularly when expressing technical requirements, constraints, implementation plans, and engineering decisions to both business and technical audiences
• You must have the authorization to work in the US to become an employee

Benefits

• Comprehensive Medical, Dental and Vision plans (ButterflyMX covers 80% of the cost) starting day 1
• 401(k) plan with a match
• 10 paid holidays, 20 vacation days, 5 sick days, 3 floating holidays
• Basic Life and Accidental Death and Dismemberment Insurance (ButterflyMX covers 100% of the cost)
• Short and Long Term Disability (ButterflyMX covers 100% of the cost)
• Paid Family Leave
• Employee Assistance Program
• Quarterly self-care stipends
• Access to optional benefits including pre-tax flexible healthcare spending accounts (FSA and HSA), Dependent Care FSA, and Commuter Benefits, as well as optional Supplemental Life, AD&D, Hospital Indemnity, Legal, Accident, Critical Illness, Pet, and Personal Liability Insurance

Company Overview