AI Application Modernization Technical Lead

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:

1. Set technical direction for delivery teams, including architecture, engineering practices, modernization approach, AI adoption patterns, and quality expectations.

2. Remain hands-on in the work by designing, coding, reviewing, testing, and troubleshooting software while helping other developers deliver well-architected solutions.

3. 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., 1. Lead a team of developers through new application builds and modernization programs while remaining actively involved in design, coding, review, testing, and troubleshooting

1. Set technical direction for projects, including architecture, integration patterns, modernization strategy, engineering standards, delivery approach, and technical risk management
2. 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
3. Architect and build fit-for-purpose agents and agentic workflows using frameworks such as LangGraph, A2A, MCP-enabled tools, or comparable technologies
4. Guide modernization of existing applications by analyzing legacy code, identifying business logic, assessing constraints, defining target architecture, and creating incremental transformation roadmaps
5. Make pragmatic architecture decisions across APIs, data models, cloud services, security, observability, integration, DevSecOps, and user experience considerations
6. Mentor developers in software engineering practices, AI-assisted delivery techniques, secure coding, automated testing, maintainable design, and effective code review
7. Collaborate with architects, product owners, business stakeholders, client technical teams, and delivery leaders to translate business needs into executable technical plans
8. Identify and manage risks in AI-generated software, including brittle code, hidden assumptions, weak tests, security issues, licensing concerns, maintainability gaps, and architecture drift
9. Create reusable patterns, accelerators, prompts, agents, reference architectures, and engineering practices that help the broader team deliver modernization work more effectively

A senior developer and technical leader who still enjoys building useful software and solving hard problems. You have seen enough delivery challenges to recognize patterns, anticipate risks, and help a team choose the right architecture and engineering approach for the situation. You have led developers through either new software development projects, application modernization efforts, or both. You know how to establish technical direction, break complex work into deliverable increments, coach developers through tradeoffs, and keep the team focused on building software that is secure, maintainable, testable, and aligned to business outcomes.

You are excited by the changes coming to software development. You have a growth mindset, actively experiment with AI-assisted development tools, and are interested in creating practical agents, workflows, and engineering practices that help teams build, understand, modernize, and operate software more effectively.

Required Technical and Professional Expertise

1. Significant hands-on software development experience delivering production-quality applications
2. Experience leading a team of developers, including mentoring, code review, technical planning, delivery guidance, and issue resolution
3. Experience setting technical direction for software delivery projects, including architecture decisions, engineering standards, delivery patterns, and technical risk management
4. Experience with at least one modern programming language such as Java, Python, JavaScript/TypeScript, C#, Go, or comparable technologies
5. Experience with either new application development, application modernization, or both
6. Practical experience using AI-assisted development tools to support coding, refactoring, testing, documentation, debugging, code comprehension, and architecture exploration
7. Experience reviewing and validating AI-generated code for correctness, security, maintainability, performance, testability, and alignment with architecture and requirements
8. Familiarity with agentic development concepts and experience building or prototyping fit-for-purpose agents using LangGraph, A2A, MCP-enabled tools, or similar frameworks
9. Strong understanding of software architecture and engineering fundamentals, including APIs, data models, integration patterns, automated testing, version control, CI/CD, secure coding, observability, and operational support
10. Ability to analyze existing codebases, identify modernization opportunities, define target-state architecture, and create pragmatic incremental transformation plans
11. Ability to communicate technical direction clearly to developers, architects, stakeholders, and client teams

12. Growth mindset and enthusiasm for how AI will reshape the software development profession Preferred Technical and Professional Experience

13. Experience modernizing legacy applications, including mainframe, Fortran, J2EE, ASP, monolithic, or other enterprise application estates
14. Experience architecting cloud-native applications, APIs, microservices, event-driven systems, or modern front-end experiences
15. Hands-on experience with LangGraph, A2A, MCP, OpenAI or Anthropic APIs, Semantic Kernel, CrewAI, or comparable agent and orchestration frameworks
16. Experience designing agents that interact with enterprise tools, repositories, documentation, tickets, CI/CD pipelines, runtime telemetry, or application data
17. Experience defining architecture guardrails, reference implementations, coding standards, reusable components, or engineering playbooks for delivery teams
18. Familiarity with DevSecOps practices, automated quality gates, observability, containerization, infrastructure as code, and secure software delivery pipelines
19. Experience with retrieval-augmented generation, vector databases, tool calling, evaluation harnesses, prompt engineering, LLM application testing, or agent observability
20. Experience working in Agile delivery environments with product owners, architects, business stakeholders, client executives, and distributed engineering teams
21. Ability to mentor and influence other developers in practical, responsible, and effective use of AI-assisted software development practices