Job Title: AI Development Lead
Location: Chicago, IL – Remote
Engagement Type: Contract
Role Overview
We are seeking a hands-on Senior/Lead AI Developer with strong technical leadership experience to triage unfamiliar enterprise applications, design modernization strategies, and build reusable AI skills and agents. You will guide development pods through safe technology-stack and security upgrades while preserving each application's intended architecture and behaviour.
Key Responsibilities
AI-Assisted Reverse Engineering: Lead the reverse engineering of legacy and current-state applications using AI agents and skills to map architecture, dependencies, integrations, database touchpoints, security flows, runtime assumptions, and deployment characteristics.
Specification & Planning: Translate reverse-engineered findings into clear technical specifications and spec-driven implementation plans for execution by AI-assisted delivery pods.
Agent & Skill Development: Design, author, refine, and govern reusable AI skills and agents for reverse engineering, dependency analysis, forward engineering, code modification, migration, remediation, and verification.
Application Modernization: Drive runtime/framework upgrades, dependency/JAR/package updates, application-server compatibility, and OS/infrastructure changes for Java and .NET applications.
Security Modernization: Lead security upgrades, including identifying LDAP/legacy authorization logic and guiding migrations to token-based identity and access patterns (Okta, OAuth, OIDC, JWT).
Architecture Preservation & Blast Radius Analysis: Focus on making applications run safely on target infrastructure without unnecessary decomposition or re-platforming. Assess blast radius across databases, interfaces, shared libraries, batch processes, downstream/upstream systems, configurations, and deployment pipelines prior to executing changes.
Pod Leadership & Execution: Break modernization work into pod-ready increments, assign tasks to developers, review agent outputs and code changes, and remain hands-on for complex or high-risk components.
Continuous Improvement: Enhance agent effectiveness across applications by capturing reusable patterns, failure modes, context requirements, prompts/instructions, and verification steps.
Cross-Functional Collaboration: Partner with AI Test Leads, architects, security, infrastructure, and application stakeholders to define acceptance criteria, quality gates, rollback considerations, and production readiness.
Troubleshooting & Mentorship: Lead technical troubleshooting and root-cause analysis (RCA) for complex failures and production-like issues. Mentor developers in agentic engineering, spec-driven development, secure coding, code review, dependency management, and human-in-the-loop verification.
Required Qualifications
7–10 years of overall IT experience working as a Software Engineer with hands-on production incident/P1 troubleshooting experience and disciplined systems thinking.
1–2 years of hands-on experience working with agentic engineering and AI projects.
Deep technical expertise in Java and .NET ecosystems (frameworks, runtimes, dependency management, and application servers).
Strong understanding of modern identity and access management patterns (Okta, OAuth, OIDC, JWT) and migrating away from legacy authorization (e.g., LDAP).
Proven technical lead experience guiding engineering teams, reviewing code, and managing high-risk deployments.
(Note: All candidates selected for an interview are required to complete a mandatory identity verification process.)
