About the role
The Role
We are seeking a hands-on Senior Software Developer / Technical Lead with an AI focus to help us lead teams that build new applications and modernize existing ones for our clients. You will work as part of an AI Led Application Modernization team that believes the way software is designed, built, tested, and maintained is changing quickly—and that senior technical leaders have an opportunity to shape how teams adopt these changes responsibly and effectively. Among your responsibilities will be:
- Set technical direction for delivery teams, including architecture, engineering practices, modernization approach, AI adoption patterns, and quality expectations.
- Remain hands-on in the work by designing, coding, reviewing, testing, and troubleshooting software while helping other developers deliver well-architected solutions.
- Use AI-assisted development tools and create fit-for-purpose agents and agentic workflows using frameworks such as LangGraph, A2A, MCP-enabled tools, or similar approaches when they are the right solution for a client or delivery challenge.
This role is both hands-on and leadership oriented. You will write code, review AI-generated output, guide architectural decisions, mentor developers, establish delivery patterns, and help teams use AI responsibly to build and modernize software faster without sacrificing quality, security, or maintainability.
Key Responsibilities
- Lead a team of developers through new application builds and modernization programs while remaining actively involved in design, coding, review, testing, and troubleshooting
- Set technical direction for projects, including architecture, integration patterns, modernization strategy, engineering standards, delivery approach, and technical risk management
- Use AI-assisted development tools to accelerate code comprehension, generation, refactoring, testing, documentation, and migration planning while ensuring that outputs are validated by experienced engineering judgment
- Architect and build fit-for-purpose agents and agentic workflows using frameworks such as LangGraph, A2A, MCP-enabled tools, or comparable technologies
- Guide modernization of existing applications by analyzing legacy code, identifying business logic, assessing constraints, defining target architecture, and creating incremental transformation roadmaps
- Make pragmatic architecture decisions across APIs, data models, cloud services, security, observability, integration, DevSecOps, and user experience considerations