Sr. Software Engineer - iOS (Swift) & Automation Testing

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.

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.