Lead reverse engineering of enterprise applications using AI agents and skills to identify architecture, dependencies, integrations, databases, security flows, runtime requirements, and deployment characteristics.
Convert findings into technical specifications and spec-driven implementation plans for AI-assisted development teams.
Design, develop, refine, and govern reusable AI skills, agents, prompts, and workflows for reverse engineering, modernization, remediation, and verification.
Lead Java and .NET modernization, including runtime/framework, JAR/package, application server, OS, and infrastructure upgrades.
Drive security modernization, including migration from legacy LDAP authorization to Okta, OAuth/OIDC, JWT, and token-based security patterns.
Assess application dependencies and blast radius across databases, APIs, interfaces, shared libraries, batch processes, configurations, and deployment pipelines.
Preserve existing application architecture and behavior where required while enabling safe operation on target platforms.
Break modernization initiatives into development-ready increments and guide engineering pods through implementation.
Review AI-generated designs and code, perform technical reviews, and remain hands-on with complex or high-risk components.
Continuously improve AI agent effectiveness by capturing reusable patterns, failure modes, context requirements, prompts, and verification techniques.
Partner with architects, AI Test Leads, security, infrastructure, and application teams to establish acceptance criteria, quality gates, rollback plans, and production-readiness standards.
Lead troubleshooting, root-cause analysis, and resolution of complex production and P1 incidents.
Mentor developers in agentic engineering, AI-assisted development, secure coding, code review, dependency management, and human-in-the-loop validation.
Required Qualifications
7–10 years of IT/software engineering experience with strong production support and incident management experience.
1–2+ years of experience with AI, agentic engineering, or AI-assisted software development.
Strong hands-on experience with Java and/or .NET application development and modernization.
Experience with application reverse engineering, dependency analysis, troubleshooting, and technical design.
Strong understanding of APIs, databases, application servers, CI/CD, infrastructure, and enterprise integrations.
Experience with LDAP, OAuth/OIDC, JWT, Okta, or comparable identity and access technologies.
Experience leading development teams or technical pods without necessarily having direct management responsibility.
Strong production troubleshooting and P1 incident/root-cause analysis experience.
Ability to review and validate AI-generated code and technical outputs.
Strong communication, technical leadership, and mentoring skills.
Preferred Qualifications
Experience building or governing AI agents, reusable AI skills, agentic workflows, or autonomous development tools.
Experience with spec-driven development and AI-assisted coding platforms.
Experience modernizing legacy enterprise applications while preserving existing architecture and behavior.
Knowledge of cloud platforms, containers, DevSecOps, automated testing, and CI/CD.