AI Development Lead

Job Description: We are looking for a Senior/Lead AI Developer with hands-on technical leadership experience to triage unfamiliar enterprise applications, design modernization approaches, develop reusable AI skills/agents, and guide development pods through safe technology-stack and security upgrades while preserving the application's intended architecture and behavior. Key Responsibilities: 7–10 years of IT experience as a Software Engineer, including production incident experience. 1–2 years of experience working with agentic engineering and AI projects. Lead reverse engineering of legacy and current-state applications using AI agents/skills. Analyze architecture, dependencies, integrations, databases, security flows, runtime assumptions, and deployment characteristics. Translate reverse-engineered findings into technical specifications and spec-driven implementation plans. Design, develop, refine, and govern reusable AI skills and agents for reverse engineering, dependency analysis, migration, remediation, and verification. Lead modernization of Java and .NET applications, including runtime/framework, dependency, application-server, OS, and infrastructure upgrades. Drive security modernization, including migration from LDAP/legacy authorization to token-based identity and access patterns using Okta, OAuth/OIDC, and JWT concepts. Preserve existing application architecture where required and focus on safe migration to target infrastructure. Assess blast radius across databases, interfaces, shared libraries, batch processes, upstream/downstream systems, configurations, and deployment pipelines. Break modernization initiatives into pod-ready increments, assign development tasks, review AI-generated outputs/code, and remain hands-on with complex components. Continuously improve AI agent effectiveness by identifying reusable patterns, failure modes, context requirements, prompts, and verification steps. Collaborate with AI Test Leads, architects, security, infrastructure, and application stakeholders to establish acceptance criteria, quality gates, rollback plans, and production-readiness standards. Lead technical troubleshooting and root-cause analysis for complex failures and production-like issues, including P1/critical incidents. Mentor developers in agentic engineering, spec-driven development, secure coding, code reviews, dependency management, and human-in-the-loop verification.