Adam Horacek
Senior / Lead iOS / macOS Engineer • AI-Native Apple Platform Engineer
Swift 6 • SwiftUI • Structured Concurrency • Agentic Development • On-Device AI • Core ML
- Tel: +420 775 622 608
- E-mail: [email protected]
- GitHub: https://github.com/adamhoracek
- LinkedIn: https://linkedin.com/in/adamhoracek
- PDF: https://adamhoracek.com/Adam-Horacek-CV.pdf
Summary
Senior iOS/macOS engineer with 15+ years building and shipping Apple-platform software across fintech, security-sensitive, and performance-critical environments. Strong in modern Swift, Swift 6 / strict concurrency, SwiftUI, architecture, CI, debugging, and production releases.
Currently focused on AI-native Apple-platform engineering: combining senior mobile architecture with agentic development workflows, local/on-device inference, and privacy-conscious LLM-assisted delivery. Experienced using and orchestrating tools such as Codex, Claude, CLI agents, repo-local instructions, skills, plugins, and task-specific agent workflows for implementation, review, migration, debugging, documentation, and verification.
Hands-on ML background including custom neural networks and classifiers, TensorFlow 2 coursework/certification, and local inference experiments using Core ML, ML Kit, and Apple-platform runtime integration. Interested in AI systems that are not just demos, but maintainable, testable, privacy-aware features embedded into real applications.
Systems thinker with strong pattern recognition, enabling fast end-to-end mental models, early detection of hidden coupling, and design for real operational constraints.
Professional experience
Independent Contractor
Senior/Lead iOS/macOS Engineer • AI-Native Apple Platform Engineer
Contract • Remote • 07/2023–Present
Freelance/contract engineering across Apple-platform codebases, with recent focus on modern Swift, AI-native development workflows, and local/on-device AI integration.
- Contract delivery across iOS/macOS/tvOS codebases
- Swift 6 migration: resolved Sendable fallout, actor-isolation refactors, strict concurrency issues, and race conditions
- Designed and used agentic development workflows with Codex, Claude, CLI agents, repo-local instructions, skills, plugins, and task-specific orchestration
- Orchestrated AI agents for implementation, refactoring, code review, migration planning, documentation, debugging, and verification
- Built AI-assisted workflows around explicit context, scoped instructions, reproducible commands, tests, review loops, and auditable changes
- Worked with local/on-device inference patterns, including connecting models into app architecture through Core ML and ML Kit
- Built personal/R&D ML systems including custom neural networks and classifiers; TensorFlow 2 certified
- Explored local inference architecture for privacy-conscious AI features close to the device/runtime boundary
- Introduced DTO boundaries to decouple UI/domain layers
- Integrated Kotlin Multiplatform (KMP) shared modules into an iOS app
- Modernized SwiftUI stack using Observation and a VM‑less MV (Model–View) approach
- Implemented Swift Charts (with Metal overlays)
- Strengthened unit, integration, snapshot, and UI tests; wired into CI
Deutsche Bank
Lead iOS Engineer
Contract • Remote • Frankfurt am Main, Germany • 09/2020–06/2023
Greenfield, modular, white‑label mobile banking + signing iOS applications.
- Designed and implemented a modular Clean Architecture with Coordinators and RxSwift
- Owned critical user flows: authentication/session lifecycle and transaction verifications
- Implemented SwiftPM-level build customization (custom code exclusion/feature gating + secure config/secrets injection at build time)
- Built CI / environment configuration patterns: secure secrets handling, env‑specific configuration, and safe release pipelines
- Drove security hardening work (threat‑model mindset, defensive coding)
- Mentored engineers via code reviews and architecture guidance
- Worked in regulated delivery environments (CI, SDLC, SAFe)
Apps shipped / contributed to
- Deutsche Bank — https://apps.apple.com/us/app/deutsche-bank/id1040475847
- Postbank — https://apps.apple.com/us/app/postbank/id6444706327
- FYRST — https://apps.apple.com/us/app/fyrst/id6447359205
- Postbank BestSign — https://apps.apple.com/us/app/postbank-bestsign/id1442251022
Deutsche Bank
Senior iOS Developer
Contract • On‑site/Remote • Frankfurt am Main, Germany • 02/2018–03/2019
Enterprise iPad applications (internal distribution; used by advisors in branches).
- Built features using Clean Swift (VIP) architecture
- Collaborated with Apple’s Enterprise Design Labs
- Diagnosed and resolved concurrency/data race issues to improve stability and performance
- Improved developer experience: deprecated brittle binary dependencies, introduced Workspaces, and reduced build friction across teams
- Strengthened testing culture (unit/UI tests) and high‑signal code reviews
VEON
Senior iOS Developer
Contract • On-site • Amsterdam, Netherlands • 12/2017–01/2018
- Modernized a high‑traffic messaging/VoIP app by migrating Objective‑C components to Swift
- Refactored toward VIPER + SOLID to improve maintainability and long‑term velocity
Sapient Nitro
Senior iOS Developer
Contract • London, UK / New Delhi, India • 04/2017–06/2017
- Delivered UI/UX improvements and new iPad features; improved iPhone app quality in collaboration with an offshore team
- Raised engineering standards via code reviews and pragmatic best practices
Apps shipped / contributed to
- European Tour — https://apps.apple.com/us/app/european-tour/id573521629
Aegon
Senior iOS Developer
Contract • On-site • The Hague, Netherlands • 11/2016–02/2017
- Re‑architected UI layers (MVC/MVVM) and implemented client‑side auth (JWT/SSO)
- Strengthened security posture through crypto‑oriented improvements and defensive coding
Qredo
Senior iOS Developer
On-site • London, UK • 10/2015–12/2015
- Consolidated Objective‑C/Swift iOS SDK
- Improved stability by fixing hundreds of failing tests
- Optimized multi‑threading/message queues and strengthened secure communications (binary protocols, Security framework)
Farm At Hand
Senior iOS Developer
On-site • Vancouver, Canada • 02/2014–07/2014
- Built a farm management iOS app (offline multi‑user support & synchronization)
- Contributed to API design, DevOps, and hiring process
Apps shipped / contributed to
- Farm At Hand — https://apps.apple.com/us/app/farm-at-hand/id1089000986
Core strengths
- Swift 6 & concurrency correctness: async/await, actors, Sendable, strict concurrency checks, TaskGroups, cancellation; race condition debugging
- SwiftUI stack: SwiftUI, Observation (@Observable), SwiftData; UIKit/AppKit interoperability
- Charts & visualization: Swift Charts, custom rendering where needed; performance tuning (Instruments, signposts), Metal when beneficial
- Synchronization: Synchronization framework (Mutex) for safe shared state where actors aren’t the right trade‑off
- Architecture: MVVM(+C) + Coordinator, Clean Architecture, Clean Swift (VIP), VIPER, MV (Model–View) SwiftUI (view‑model‑less / Observation‑driven)
- Systems thinking (pattern‑first cognitive style): tends to process information differently, surfacing hidden coupling, edge cases, and second‑order effects early; translates that into pragmatic architecture and clean interfaces.
- Quality & delivery: Swift Testing / XCTest, UI tests, snapshot tests, integration tests, CI/CD, code review, SDLC/SAFe environments
- Security mindset: auth/session design, secure config handling, reverse‑engineering awareness
AI-native / agentic development
- Agentic workflows: Codex, Claude, CLI agents, repo-local instruction files, skills, plugins, and task-specific orchestration
- LLM workflow design: context shaping, prompt/instruction design, multi-step task decomposition, tool routing, verification loops, and human-reviewed output
- Software delivery with agents: using LLM agents for implementation, refactoring, test creation, documentation, migration planning, debugging, and review support
- On-device AI: Core ML, ML Kit, local inference architecture, Apple-platform model integration
- ML foundations: custom neural networks/classifiers, TensorFlow 2, model training/evaluation basics
- Privacy-first practice: no secrets/client-data leakage, minimal/redacted context, policy-compliant usage, and reviewed/tested output before integration
Skills
- Languages: Swift, Objective‑C, C/C++, Python, JavaScript, Bash
- Platforms: iOS, iPadOS, macOS, tvOS
- UI: SwiftUI, UIKit, AppKit
- Modern Swift: Swift 6, Structured Concurrency (async/await, actors, Sendable), Synchronization (Mutex), GCD (legacy/interop)
- Frameworks: Observation, Swift Charts, SwiftData, Core Data, Combine/RxSwift (interop), Swift‑NIO (when applicable), Metal
- AI / Agentic development: Codex, Claude, CLI agents, skills/plugins, agent orchestration, LLM workflows, prompt/instruction design, verification loops
- AI / ML: Core ML, ML Kit, local/on-device inference, TensorFlow 2, neural networks, classifiers
- Testing: Swift Testing, XCTest, UI Testing, snapshot tests, integration tests
- Architecture: MVVM(+C) + Coordinator, Clean Architecture, Clean Swift (VIP), VIPER, MV (Model–View) SwiftUI (view‑model‑less / Observation‑driven)
- Tooling: Xcode, Instruments, Swift Package Manager, Git, Charles Proxy, Wireshark, Figma
- CI/DevOps: GitHub/GitLab, CI pipelines, secure environment config
Selected projects (personal / R&D)
Local AI / On-Device Inference R&D
Apple-platform R&D around local model integration, privacy-conscious inference, and app/runtime boundaries.
- Connected local models into Apple-platform app architecture using Core ML and ML Kit
- Explored local inference pipelines, model boundaries, runtime constraints, and offline-first AI behavior
- Built ML foundations through custom neural networks and classifiers using TensorFlow 2
- Focused on privacy, device-local execution, explicit data boundaries, and maintainable integration into real app architecture
Quantitative Trading (Personal Project)
macOS trading workstation focused on high‑performance visualization and backtesting.
- Real‑time chart rendering, indicators, and backtesting engine
- Broker API integrations (architecture‑ready for multiple providers)
- Tech: Swift, SwiftUI, AppKit, SwiftData, Swift Concurrency, Metal, Swift Charts
BitTorrent + DHT (Personal Project)
Custom BitTorrent client with a DHT implementation for decentralized peer discovery.
- Tech: Swift, Swift‑NIO, networking protocols, distributed systems concepts
Education
- Masaryk University — Czechia (Parallel and Distributed Systems) — 2010–2011
- Charles University — Czechia (General Computer Science) — 2007–2009
Courses
- Claude Code in Action, Anthropic — https://verify.skilljar.com/c/ynuxkpki9wj6
- Getting started with TensorFlow 2, Imperial College London — https://www.coursera.org/account/accomplishments/verify/2SNBXJ9KDZBM
Languages
- English — C2
- Czech / Slovak — C2
- German — B1