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.