Required Skills:

Strong experience in Ruby, with working knowledge of Python for machine learning and statistical analysis, and familiarity with Go for high-performance needs

Demonstrated daily use of Claude Code as a primary agentic coding tool, with production PRs to show for it, not just experimentation

Experience building and coordinating multi-agent workflows with proper checkpointing, reproducibility, and cost control

Ability to author and maintain context documents (CLAUDE.md, architecture maps, runbooks) that make a codebase AI-navigable

Experience designing evaluation harnesses to catch regressions and measure AI-assisted velocity

Disciplined prompt engineering: you design prompts with intent, iterate systematically, and document what works

Experience with RAG systems, MCP servers, or multi-agent orchestration

Security-first mindset around AI workflows: data classification, secrets hygiene, prompt injection awareness

Strong fundamentals in system design, debugging, and architecture reasoning

Ability to teach and share knowledge in ways that genuinely move a team forward

Excellent communication and collaboration skills

Job Responsibilities:

Demonstrate total fluency in Ruby on Rails and at least one modern front-end environment, while maintaining the confidence and adaptability to work in any codebase on any platform by leveraging AI coding agents effectively.

Operate daily with Claude Code using structured, repeatable workflows: plan, decompose, implement, test, ship

Know when to trust AI output and when to verify it. You are the quality gate, not the rubber stamp

Review AI-generated code with discipline: know what patterns to trust, where to focus attention, and when to regenerate vs. fix manually

Use AI for planning before code exists: technical design, task decomposition, risk identification, and effort estimation

Serve as a technical resource for AI-augmented workflows across the engineering team, sharing playbooks, patterns, and tooling that help other developers level up

Build reusable agent skills, hooks, and guardrails that raise the team-wide baseline

Collaborate with product managers, front-end developers, and linguists across cross-functional teams

Participate in code reviews, sprint planning, and agile processes

Continuously research and evaluate new AI tools, models, and techniques with a framework for deciding what to adopt

Who You Are:

You are a top-tier engineer who can perform the work of your agents and more; you use AI not to compensate for a lack of skill, but to amplify your already superior capability and accelerate delivery. You do not treat AI as a shortcut. You treat it as infrastructure. You have built workflows, not just prompts. You understand context engineering. You know when to let the agent run and when to take the wheel. You verify the output because you own the result. You measure your process and improve it. When AI produces poor results, your first question is what you can change, not what AI cannot do.

You are also someone who takes initiative and ownership. At Mango, we hold ourselves accountable to results, we find a way, and we passionately pursue excellence and continuous improvement. If that describes how you already work, you will feel at home here.