Lead Agentic AI Engineer

Primary Responsibilities

• 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.
• Experience implementing AI-assisted reverse engineering, code migration, remediation, or application modernization.
• Experience working with regulated or large-scale enterprise environments.