Agentic-First Software Engineer (Relocate to Miami)

Jiffy•Austin, TX

2h•$150,000 - $265,000

About The Position

Jiffy.com is hiring an Agentic-First Software Engineer at the Senior, Staff, or Principal level to orchestrate AI coding agents and deliver production software across its e-commerce platform. The role owns end-to-end features spanning the storefront, checkout, internal tools, and platform services, coordinating multiple AI-driven work streams. Engineers direct agents such as Claude Code, Codex, and Cursor to produce, test, review, and deploy code; the human engineer supplies architectural judgment, critical review, quality assurance, and production ownership. Reporting to an Engineering Manager, the engineer works closely with Product, General Managers, Design, Operations, and other engineering teams. The role also contributes to Jiffy's internal AI tooling and shared skills and rules library, improves AI-native engineering workflows, and mentors colleagues in agent orchestration. Applicants must be authorized to work in the United States without employer sponsorship now or in the future.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field.
At least 5 years of professional software engineering experience shipping production systems at scale.
Hands-on experience using AI coding agents such as Claude Code, Codex, Cursor, or equivalent as a primary development tool; must be able to discuss real work delivered through agent orchestration.
Ability to run multiple agents in parallel and manage concurrent work streams while maintaining quality, context, and accountability.
Strong software design fundamentals, including object-oriented design, API design, data modeling, distributed-system reliability, and performance.
Proficiency in at least one server-side language (such as Ruby, Python, Go, or Java) and one modern front-end stack (such as React/TypeScript or equivalent).
Experience with relational databases such as Postgres or MySQL, SQL, and building or consuming REST or GraphQL APIs.
Strong code-review skills, including the ability to read, critique, and correct diffs quickly.
Strong written communication skills for expressing intent, writing pull request descriptions, and creating prompts.
High integrity, accountability, ownership, and commitment to quality.
Willingness to work in a fast-paced, ambiguous, high-autonomy environment.
Legally authorized to work in the United States without employer sponsorship now or in the future.

Nice To Haves

Experience authoring or extending AI developer tooling such as custom skills, slash commands, MCP servers, sub-agents, evaluation harnesses, or team prompt libraries.
Experience with Ruby on Rails and Solidus/Spree or other large-scale e-commerce platforms.
Experience with React 19, TypeScript, GraphQL (Apollo), Tailwind, and modern state management such as React Query, XState, or Jotai.
Experience operating services on Kubernetes, including Istio, KEDA, or Flagger, and using modern observability stacks.
Experience maintaining and extending automated test suites with Playwright, Vitest, and RSpec, including through agent workflows.
A track record of mentoring engineers on AI-native workflows, publishing internal patterns, or leading an organization away from manual coding.
Documented improvements in features per week, cycle time, or review time attributable to AI adoption.
Experience shipping in a fast-paced, agile environment at a high-growth startup or technology company.

Responsibilities

Orchestrate AI coding agents across 3–6 concurrent work streams, using worktrees, sub-agents, and background tasks.
Own features end-to-end: translate product intent into specifications, decompose work into agent-executable plans, guide implementation, critically review diffs, run QA, land pull requests, and verify production health.
Design and architect scalable, reliable systems across Rails 8/Solidus, GraphQL APIs, a React 19 front end, and Kubernetes infrastructure.
Review AI-generated code for hallucinated APIs, security, idiomatic patterns, and structural quality.
Build and evolve internal AI tooling, including skills, rules, prompts, MCP integrations, and evaluation harnesses; contribute to the shared .ai/ skills and rules library.
Drive meaningful test coverage using RSpec, Vitest, and Playwright; monitor deployments, respond to incidents, and own shipped services.
Partner with Product, Design, Operations, and engineering teams to define and ship features; participate in architecture and code reviews.
Mentor engineers on AI-native workflows and orchestration patterns.
Identify manual work in QA, operations runbooks, data investigations, and migrations that can be replaced by agents, and automate it.