Sobre este puesto de Sr. Software Engineer - iOS (Swift) & Automation Testing en GSSTech Group
We are looking for an experienced iOS Software Engineer with strong hands-on expertise in Swift and modern iOS development, along with experience in automation testing, to build and maintain large-scale, modular iOS applications.
The ideal candidate will have experience designing scalable iOS architectures, developing high-quality applications for iPhone and iPad, optimizing application performance, and working with modern Apple technologies.
The role also requires hands-on experience with AI/LLM integration, including LLM APIs, Model Context Protocol (MCP), token management, context handling, agentic workflows, multi-agent orchestration, and tool-use patterns in production environments.
Requirements
Key Responsibilities
- Design, develop, and maintain large-scale, modular iOS applications using Swift.
- Build scalable, maintainable, testable, and high-performance solutions across multiple feature teams.
- Develop advanced SwiftUI interfaces with a strong focus on responsiveness, usability, and accessibility.
- Design and implement scalable application architectures and modern architectural patterns.
- Develop and maintain automated testing solutions to ensure application quality and reliability.
- Integrate and work with LLM APIs within production iOS applications.
- Implement and work with MCP (Model Context Protocol) frameworks in production environments.
- Work with token management, context handling, and agentic workflows within AI-powered applications.
- Implement multi-agent orchestration and tool-use patterns where applicable.
- Evaluate LLM trade-offs and design resilient error-handling mechanisms for AI-powered applications.
- Diagnose and resolve memory, performance, concurrency, and application stability issues using Xcode Instruments and profiling tools.
- Implement robust crash monitoring and observability solutions.
- Analyze crash trends and production issues and drive improvements in application stability.
- Optimize application startup performance, memory usage, responsiveness, and overall runtime performance.
- Apply modern dependency management approaches to maintain scalable and modular application architecture.
- Collaborate with multiple feature teams to establish consistent engineering and architectural practices.
- Participate in code reviews, technical discussions, debugging, testing, and continuous improvement initiatives.
- Troubleshoot complex production issues and ensure reliable application delivery.
Core Technical Requirements
- Strong hands-on experience in iOS application development using Swift.
- Experience building large-scale and modular iOS applications.
- Strong experience with SwiftUI and modern Apple development technologies.
- Strong understanding of iOS application architecture and scalable architectural patterns.
- Experience developing applications for iPhone and iPad.
- Experience with automation testing for iOS applications.
- Hands-on experience with LLM APIs and AI-powered application development.
- Production experience with MCP (Model Context Protocol) frameworks.
- Understanding of:
- Token management
- Context handling
- Agentic workflows
- Multi-agent orchestration
- Tool-use patterns
- LLM trade-offs
- Resilient error handling for AI applications
- Strong experience with Xcode Instruments and profiling tools.
- Experience diagnosing and resolving:
- Memory leaks
- Memory issues
- Performance bottlenecks
- Concurrency issues
- Application crashes
- Experience with crash monitoring, observability, and production diagnostics.
- Experience with modern dependency management.
Specialized Expertise
Candidates should have strong hands-on specialization in 2–3 or more of the following areas:
1. Swift Concurrency
- async/await
- Actors
- Task Groups
2. SwiftUI & Combine
- Advanced SwiftUI development
- Combine framework
- Responsive and reactive UI development
3. Core Data / SwiftData
- Data persistence
- Core Data or SwiftData implementation
4. Networking
- URLSession
- gRPC
- Protocol Buffers
5. Background Processing
- BackgroundTasks framework
- Background execution and task management
Performance, Stability & Observability
The candidate should have practical production experience with:
- Memory leak detection and troubleshooting using Instruments
- CPU and memory profiling
- Performance analysis and optimization
- Application startup optimization
- Concurrency issue diagnosis
- Crash monitoring and analysis
- Crash trend analysis
- Production debugging
- Application observability and stability improvements
AI / LLM Requirements
Strong practical experience with AI integration is required, including:
- Integration of LLM APIs
- Production implementation of MCP (Model Context Protocol)
- Token and context management
- Agentic application workflows
- Multi-agent orchestration
- Tool-use patterns
- Evaluation of LLM model trade-offs
- Error handling and resilience in AI-powered applications
Automation & Quality
- Experience building or maintaining iOS automation testing frameworks/scripts.
- Strong understanding of software testing and quality engineering practices.
- Experience integrating testing into development and CI/CD workflows.
- Ability to write maintainable and reliable automated tests.
- Experience identifying, reproducing, debugging, and resolving application defects.
Required Competencies
- Strong problem-solving and debugging skills.
- Strong understanding of software engineering best practices.
- Ability to work on complex production applications.
- Strong ownership of application quality, performance, and reliability.
- Ability to collaborate effectively across multiple feature teams.
- Strong communication and teamwork skills.
- Ability to learn and adapt to modern iOS and AI technologies.
- Comfortable working in a fast-paced Agile engineering environment.
Preferred Experience
- Experience working on large-scale digital products or banking applications.
- Experience in banking, financial services, or digital payments.
- Experience working with enterprise-scale mobile applications.
- Experience integrating AI/LLM capabilities into production applications.
- Experience working with modern CI/CD and engineering automation practices.