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. 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.