Director, Enterprise AI Business Applications

Location: Rosslyn, VA

Reports To: CIO

Employment Type: Full‑time, onsite

Position Overview

Hanwha Defense USA (HDUSA) develops and supplies advanced ground and sea combat systems to strengthen the capabilities of U.S. and allied forces. HDUSA has built an internal enterprise application ecosystem where AI is not a feature added at the end—nearly every application is either built with AI or has AI integrated into how it works. The Director of Enterprise AI Business Applications will own that ecosystem and scale it. This role leads the internal application team, serves as product owner for internally built applications, owns the SaaS and on‑premise applications purchased, and is the go‑to when anything in that portfolio breaks. The role is hands‑on: shipping software, reviewing team output, and setting the technical standards for the organization.

Essential Duties and Responsibilities

• Enterprise Application Portfolio Ownership: Own the full portfolio of HDUSA business applications (both built and purchased) across their lifecycle—from selection/design through sustainment and retirement. Serve as the escalation point for any issue, evaluate and integrate point solutions, manage vendor relationships, licenses, and decisions to keep or replace. Maintain visibility into what the company runs, costs, ownership, data holdings, and integrations. Apply financial understanding of product ROI to ensure tangible value.
• Product Ownership: Act as product owner for internally built enterprise applications. Set roadmaps, write and prioritize backlogs, define requirements, and control scope in an aggressive agentic‑AI development environment. Work directly with stakeholders across Finance, Contracts, Supply Chain, Manufacturing, Engineering, Program Management, Security, IT, and HR to design systems that reflect actual work. Own adoption, define success measures, and report on them.
• Engineering Practice and Delivery: Own the software delivery lifecycle for the internal team, including source‑control strategy, branching, code review, environment management, testing, release, and rollback. Build and maintain CI/CD pipelines; automated build, test, and deployment are baseline expectations. Establish standards for logging, monitoring, error handling, and observability. Ship code personally, review team code, keep technical debt visible, and manage production operations (incident response, root‑cause analysis, uptime, backup/restore, recovery testing). Ensure long‑term maintainability through dependency upgrades, deprecations, data migrations, and backward compatibility.
• Agentic AI Architecture and Integration: Own AI architecture within HDUSA applications, including model selection, routing, retrieval over internal data, tool/API calling, context management, and evaluation. Design and implement multi‑agent patterns, agent‑to‑agent communication, orchestration across services, and handoff/escalation logic between automated steps and human decision points. Choose appropriate frameworks and integration strategies, embed evaluation and testing into AI features, and embed security from the start (prompt injection, tool abuse, permission scoping, data leakage, third‑party model risk, audit trails).
• Security, Compliance, and Governance: Ensure applications and AI capabilities meet CUI, ITAR, export‑control, and FOCI‑mitigated access requirements. Work within HDUSA AI governance to route sensitive/export‑controlled data to approved environments and control model/tool access. Partner with IT Security and Compliance on security reviews, access control, logging, and audit evidence. Apply the same standards to purchased software as to built solutions (data residency, retention, subprocessors, vendor data handling).
• Team Leadership and Scaling: Lead and grow the enterprise application team—hire, onboard, set standards, and mentor. Scale the ecosystem aggressively while preserving quality, security, and maintainability. Build shared patterns, services, identity, and data across applications. Provide clear status, risk, and roadmap reporting to senior leadership. Perform other duties as assigned.

Qualifications and Experience

• 8+ years of professional software engineering experience, with at least 3 years accountable for the output of other engineers.
• Proven track record of writing production code, owning systems in production over multiple years, and being responsible for failures.
• Experience inheriting, maintaining, refactoring, or replacing systems you did not originally write.
• Established engineering standards (code review, testing, release practice) and enforced them.
• Leadership experience in software delivery (engineering manager, tech lead, or founding engineer) with accountability for team shipments.
• Hands‑on CI/CD experience: built pipelines, not just used them.
• Strong understanding of agentic AI systems, frameworks, orchestration, and integration strategies.
• Demonstrated product ownership: turning ambiguous business problems into usable products.
• Experience owning third‑party applications (selection, integration, vendor management, support).
• Security‑by‑design mindset for applications and AI systems.
• Excellent communication with both engineers and business stakeholders, including senior leadership.
• Willingness to work hands‑on alongside the team.
• U.S. citizen eligible for a U.S. Government security clearance.

Preferred Qualifications

• Experience in a regulated industry (defense, aerospace, financial services, healthcare, or critical infrastructure).
• Experience integrating enterprise data (ERP, data warehouses, internal APIs).
• Background building an application or platform team from a very small starting point.
• Familiarity with government cloud environments and associated constraints.
• Domain knowledge in manufacturing, engineering, or program execution.
• Experience mentoring junior engineers, especially those using AI‑assisted development.

Education

Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent work experience. Demonstrated ability is valued more than the credential.

Special Knowledge and Skills

• Genuine enthusiasm for AI and its impact on software development.
• Strong architectural judgment—knowing which patterns scale.
• Bias toward shipping balanced with discipline to avoid unsafe releases in regulated environments.
• Ability to operate effectively within a FOCI‑mitigated organization.
• Clear communication with engineers, business stakeholders, and senior leadership.

Physical Demands and Work Environment

Standard HDUSA physical and travel requirements per company policy.