AI Development Lead Location: 100% Remote

Job Description

We are seeking a Senior AI Development Lead with strong software engineering experience and hands-on expertise in agentic AI development, application modernization, and enterprise production support. The ideal candidate will lead AI-assisted modernization of legacy Java and .NET applications by using AI agents and reusable skills to analyze unfamiliar codebases, identify dependencies, develop technical specifications, and guide development teams through secure framework, runtime, and infrastructure upgrades. This role requires a hands-on technical leader who can combine traditional software engineering expertise with agentic coding tools such as Claude Code, Cursor, and GitHub Copilot while ensuring code quality, security, architectural integrity, and production readiness.

Key Responsibilities

Reverse engineer enterprise applications to understand architecture, dependencies, integrations, databases, security controls, and deployment environments. Design, build, configure, and improve reusable AI agents and skills for code analysis, application modernization, dependency upgrades, remediation, and verification. Lead modernization of Java and .NET applications, including JDK, framework, JAR/package, application server, operating system, and infrastructure upgrades. Create technical specifications and implementation plans for AI-assisted development teams. Identify legacy LDAP authentication and authorization mechanisms and support migration to modern identity solutions using Okta, OAuth, OIDC, and JWT. Evaluate the impact of changes across databases, APIs, shared libraries, batch processes, integrations, and deployment pipelines. Break complex modernization initiatives into manageable development tasks and guide developers through implementation and code reviews. Troubleshoot complex application failures, perform root-cause analysis, and support production incidents, including P1 issues. Establish quality gates, automated testing, security checks, human verification steps, and rollback plans. Collaborate with architects, AI Test Leads, security teams, infrastructure teams, and application stakeholders. Mentor developers on agentic engineering, spec-driven development, secure coding, and AI-assisted software delivery. Required Skills 7–10 years of overall IT experience in software engineering, including production support and incident management. 1–2 years of hands-on experience with agentic AI engineering or AI-assisted software development projects. Demonstrated experience building or configuring AI agents and reusable skills for software engineering workflows. Experience with Claude Code, Cursor, GitHub Copilot, or comparable agentic coding tools; Claude Code is strongly preferred. Strong expertise in Java and/or .NET application development, with a preference for enterprise Java modernization. Experience with JDK upgrades, JBoss or other application servers, Maven/Gradle, dependency management, and application deployments. Working knowledge of Linux/Red Hat and Windows application environments. Understanding of LDAP authentication and authorization, identity management, Okta, OAuth/OIDC, and JWT. Strong knowledge of APIs, SQL, databases, integrations, Git, CI/CD, debugging, logging, and observability. Experience with technical design documentation, spec-driven development, code reviews, automated testing, and production deployments. Strong analytical and troubleshooting skills, with the ability to assess unfamiliar applications and identify technical risks. Ability to validate AI-generated code and recommendations through testing, engineering reviews, and human approval. Preferred Skills Python programming and modern LLM or AI agent frameworks. MCP/tool integration, prompt engineering, and context engineering. GCP, Vertex AI, or other enterprise AI platforms. Application security, vulnerability remediation, secrets management, and software supply-chain security. Experience modernizing large monolithic applications while preserving existing architecture and avoiding unnecessary microservices decomposition. Ideal Candidate The ideal candidate is a hands-on software engineering leader who combines enterprise application modernization experience with practical agentic AI development skills. They should be comfortable analyzing unfamiliar systems, developing reusable AI-driven engineering workflows, leading technical teams, and ensuring that all modernization changes are secure, tested, and production-ready.