IOS AI Embedded Engineer

Core Expertise

• Experience operating modern AI-assisted development tools (e.g., Cursor, Claude Code, Codex).
• Ability to perform deep repository and git-history analysis to map out legacy codebases and structure them for LLMs.
• Excellent communication and coaching skills to lead engineering workshops and conduct workflow interviews.
• Fluent English for direct client communication.

• Strong competency in iOS/Swift development (SwiftUI/UIKit experience).
• Experience operating modern AI-assisted development tools (e.g., Cursor, Claude Code, Codex).
• Ability to perform deep repository and git-history analysis to map out legacy codebases and structure them for LLMs.
• Excellent communication and coaching skills to lead engineering workshops and conduct workflow interviews.
• Fluent English for direct client communication.

• Understanding of CI/CD constraints, particularly macOS-VM virtualisation and Namespace runners.
• Familiarity with building local pre-flight CI skills to catch build failures early.
• Prior experience working in an AI Software Factory model, including knowledge of Limestone's open-source accelerators (Velocity Core, Developer Intelligence).
• Experience in the VPN, mobile security, or telecommunications app space.

• Embedded with the client's iOS team for a 1-month Foundation phase to map their Swift codebase, identifying active code, legacy systems, and repeating patterns.
• Conduct 30-minute workflow interviews with the Head of iOS and 3-4 engineers to inventory tooling and identify repetitive, slow, or frustrating tasks.
• Ship a tailored AI toolkit directly to the iOS team within the first 7 days, including task-specific agents, commands, hooks, and local pre-flight CI skills.
• Build a versioned, agent-readable knowledge base inside the client's repository (covering spec-driven development, review patterns, etc.).
• Establish a cost telemetry baseline for AI/LLM API spend across the iOS team.
• Deliver two team-wide workshops: "Spec-driven development with AI" (90 mins) and "The AI Factory blueprint" (60 mins).
• Create a final Foundation handoff document that summarises findings and tools shipped, and lays out the recommended starting point for the Phase 2 Velocity Pod.

The project objective is to ope rationalise agentic engineering and shift the client's iOS engineering team to an AI-first baseline. This role will serve as the initial "Foundation Embed," tasked with doing a structured pass on the client's legacy iOS/Swift codebase to make it agent-readable. The engineer will deploy a tailored AI toolkit, build an agent-readable knowledge base, and level up the team's AI fluency to prepare the infrastructure for a Phase 2 Velocity Pod rollout.