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. iOS AI Embedded Engineer Requirements 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. Nice-to-Have 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. Responsibilities 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. About the project The project objective is to operationalise 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. #J-18808-Ljbffr Limestone Digital