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 up-to-date 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

📌 Sr. Software Engineer (Bengaluru)
🏢 GSSTech Group
📍 Bengaluru