Senior Software Developer / Technical Lead with an AI Focus

Kyndryl•Dallas, TX

7d•$143,640 - $327,600

About The Position

Kyndryl is seeking a hands-on Senior Software Developer / Technical Lead with an AI focus for its AI Led Application Modernization team. The role leads teams building new applications and modernizing existing ones, while remaining actively involved in software design, coding, reviewing, testing, and troubleshooting. The technical lead establishes architecture and engineering direction, delivery patterns, modernization strategies, AI adoption practices, and quality expectations. They use AI-assisted development tools and may build fit-for-purpose agents and agentic workflows with frameworks such as LangGraph, A2A, MCP-enabled tools, or comparable technologies. The role guides application modernization by analyzing legacy code and business logic, assessing constraints, defining target architectures, and developing incremental transformation roadmaps. It includes making pragmatic decisions across APIs, data models, cloud services, security, observability, integration, DevSecOps, and user experience; mentoring developers; collaborating with architects, product owners, business stakeholders, client technical teams, and delivery leaders; and managing risks associated with AI-generated software. The lead also creates reusable patterns, accelerators, prompts, agents, reference architectures, and engineering practices for broader delivery teams. The position is part of Kyndryl’s Consultant Profession and AI Led Application Modernization team, which builds new user-centric applications and modernizes varied application estates. The team operates with a startup mentality and uses and improves Kyndryl’s Agentic Framework. The U.S. compensation range is $143,640–$273,000 for a full-time schedule, with different ranges for specified locations. The position is eligible for a discretionary annual bonus, subject to plan terms, and may include a benefits package with medical and dental coverage, disability, retirement benefits, paid leave, and paid time off. Applications are accepted on a rolling basis.

Requirements

At least 7 years of hands-on software development experience delivering production-quality applications.
Experience leading a team of developers, including mentoring, code review, technical planning, delivery guidance, and issue resolution.
Experience setting technical direction for software delivery projects, including architecture decisions, engineering standards, delivery patterns, and technical risk management.
Experience with at least one modern programming language such as Java, Python, JavaScript/TypeScript, C#, Go, or comparable technologies.
Experience with new application development, application modernization, or both.
Practical experience using AI-assisted development tools for coding, refactoring, testing, documentation, debugging, code comprehension, and architecture exploration.
Ability to review and validate AI-generated code for correctness, security, maintainability, performance, testability, and alignment with architecture and requirements.
Familiarity with agentic development concepts and experience building or prototyping fit-for-purpose agents using LangGraph, A2A, MCP-enabled tools, or similar frameworks.
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.
Ability to analyze existing codebases, identify modernization opportunities, define target-state architecture, and create pragmatic incremental transformation plans.
Ability to communicate technical direction clearly to developers, architects, stakeholders, and client teams.
Growth mindset and enthusiasm for how AI will reshape software development.
Ability to lead developers through complex delivery challenges, anticipate risks, and select appropriate architecture and engineering approaches.

Nice To Haves

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

Responsibilities

Lead developers through new application builds and modernization programs while participating 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 for code comprehension, generation, refactoring, testing, documentation, and migration planning, validating outputs with engineering judgment.
Architect and build fit-for-purpose agents and agentic workflows using LangGraph, A2A, MCP-enabled tools, or comparable technologies.
Analyze legacy code and business logic, assess constraints, define target architectures, and create incremental transformation roadmaps.
Make architecture decisions involving APIs, data models, cloud services, security, observability, integration, DevSecOps, and user experience.
Mentor developers in engineering practices, AI-assisted delivery, secure coding, automated testing, maintainable design, and code review.
Collaborate with architects, product owners, business stakeholders, client technical teams, and delivery leaders to turn business needs into technical plans.
Identify and manage risks in AI-generated software, including brittle code, hidden assumptions, weak tests, security issues, licensing concerns, maintainability gaps, and architecture drift.
Create reusable patterns, accelerators, prompts, agents, reference architectures, and engineering practices to improve modernization delivery.
Guide teams in breaking complex work into deliverable increments and making appropriate architecture and engineering tradeoffs.
Gather and document customer requirements, translate stakeholder needs into functional and nonfunctional specifications, and advise customers on application selection, customization, compatibility, and deployment considerations.