This hands-on, AI-native Full Stack Developer role is part of a small team with a large mandate, where each hire significantly shapes the product and delivery approach. You will work daily alongside AI coding agents to deliver production-quality frontend, backend, database, and integration work end-to-end, ensuring correctness, security, testing, and readiness for review. You will also support client delivery by translating business requirements into technical specifications and demoing working solutions to stakeholders.

Responsibilities

Build and ship frontend and backend features end-to-end for Iris and client-facing products, covering UI, API, and database schema.
Use AI coding agents (e.g., Claude Code) as a core part of daily development workflow to produce first drafts of features.
Run multiple agents or workstreams in parallel across concurrent tickets and context-switch cleanly without losing quality.
Review, refactor, and QA your own work before handoff, catching hallucinations, security anti-patterns, logic errors, and regressions in agent-generated code.
Verify implementations against acceptance criteria and ensure submitted work meets the bar for final PR approval by the Senior Full Stack Developer.
Implement against shared contracts (interfaces, abstract classes, shared data models) and flag gaps or inconsistencies encountered during development.
Write automated tests at unit, integration, and end-to-end levels, including writing tests before code in collaboration with the Engineer in Test.
Integrate with RESTful and GraphQL APIs and contribute to internal API contract design for multi-service architectures.
Support CI/CD pipeline configuration, cloud environment setup, and deployment automation for internal and client-facing systems.
Act as a technical point of contact for clients during delivery engagements by translating business requirements into technical specifications and demoing working solutions to stakeholders.

Required Qualifications

1–3 years of professional software engineering experience (internships, apprenticeships, and demonstrated project work count).
Working proficiency in at least one modern backend language (Node.js/TypeScript, Python, or Go) and one frontend framework (React, Next.js, or equivalent).
Hands-on experience building full-stack features end-to-end, including database schema and UI (not just consuming APIs designed by others).
Practical, daily experience using at least one AI coding agent (e.g., Claude Code, GitHub Copilot, Cursor, or equivalent) as a core part of the development workflow.
Demonstrated ability to run parallel, agent-assisted workstreams and context-switch across multiple projects or tickets without losing quality.
Comfort reading, reviewing, and correcting AI-generated code, including identifying hallucinations, security anti-patterns, and logic errors.
Working knowledge of automated testing (unit, integration, end-to-end), including writing tests before code.
Basic working knowledge of cloud infrastructure fundamentals: containerization, managed databases, or serverless compute on AWS, GCP, or Azure.

Preferred Qualifications

Familiarity with Model Context Protocol (MCP) tooling, LLM orchestration patterns, or agent SDK frameworks.
Experience integrating with third-party APIs, CRMs, or building agent-driven automation (e.g., messaging platforms, email, webhook-driven workflows).
Experience authoring BRDs/PRDs or scoping documents that separate genuinely-built functionality from demo/simulated functionality.
Exposure to government, enterprise, or other regulated-industry delivery contexts.
Contributions to hackathons, open-source projects, or other public technical work demonstrating initiative.
Ability to learn and adapt as AI tools and frameworks change.