Director, AI Assisted Software Engineering
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Job Description
AI engineering director scaling enterprise AI-assisted software development at GDIT, a government technology and mission services company. Leading architecture, engineering teams, tooling, and organizational adoption.
Responsibilities:
- Build and scale the organization’s AI-Assisted Development capability
- Establish strategy, operating model, practices, and technical foundations for AI-enabled software development
- Transform how teams design, build, test, and deliver software solutions and products
- Evaluate and rationalize AI-enabled tools and platforms across the organization
- Become the internal expert on AI-enabled tool use and integration
- Define best practices and upskill engineering teams
- Operationalize AI-assisted development as an enterprise capability for market delivery
- Provide technical leadership, architecture, go-to-market support, organizational change management, and hands-on engineering expertise
- Define roadmaps, capability models, adoption strategies, and optimized engineering operating models
- Identify and implement team composition, sprint planning, code review, and delivery practices
- Build developer education programs, playbooks, best practices, and communities of practice
- Provide architectural guidance on AI-driven design patterns, quality models, and delivery processes
- Drive technical vision, architecture standards, and execution across complex multi-team programs
- Lead full SDLC and product lifecycle delivery in agile and hybrid environments
- Develop and integrate full-stack software solutions across multiple platforms and frameworks
- Translate technical concepts for non-technical stakeholders and influence senior leadership
- Drive organizational adoption of emerging AI, development, and architecture trends
- Travel less than 10%
Requirements:
- BA/BS in Computer Science, Engineering, or related field, or equivalent experience
- 5+ years of progressive software engineering experience
- 3–5+ years in technical leadership roles required
- Proven experience building and leading high-performing engineering teams, including coaching, mentorship, and capability development
- Must be able to obtain and maintain a Secret clearance
- US Citizenship required
- Strong understanding of AI-enabled development workflows, including prompt engineering, code-generation improvement loops, safety/quality validation, and architectural impacts
- Ability to identify, track, and articulate ROI associated with AI and agentic automation
- Experience assessing organizational AI-development maturity and defining roadmaps, capability models, and adoption strategies
- Direct experience evaluating, selecting, and operationalizing AI-enabled development tools such as GitHub Copilot, Azure AI, OpenAI models, and Claude Code
- Hands-on experience with LLM-based frameworks and retrieval-augmented generation (RAG)
- Experience identifying, hiring, coaching, and scaling engineers in AI-assisted development techniques
- Experience creating developer education programs, playbooks, best practices, or communities of practice
- Experience functioning as an internal SME providing architectural guidance
- Ability to drive technical vision, architecture standards, and execution across complex, multi-team programs
- Experience leading full SDLC and product lifecycle delivery in agile and hybrid environments
- Experience implementing CI/CD, DevSecOps, TDD/BDD, automation frameworks, and quality engineering practices
- Experience developing solutions within distributed, cross-functional, or geographically dispersed teams
- Full-stack development experience across multiple programming languages, including Java, JavaScript, Python, and .NET
- Hands-on experience with front-end and back-end frameworks such as Angular, React, Spring Boot, Django, and Next.js
- Experience integrating solutions across operating systems and PaaS platforms such as Linux, Unix, RHEL, and OpenShift
- Deep experience with API/web service design, secure coding standards, and scalable architectural patterns
- Preferred: understanding of Federal acquisition and security compliance, including FedRAMP and ATO implications
- Preferred: experience building enterprise AI-assisted development capabilities or platforms
- Preferred: experience productizing internal capabilities into customer-facing solutions or services
- Familiarity with AWS, Azure, GCP, and related AI/ML services
- Experience managing vendor relationships with OEMs and ISVs
- Expertise with CI/CD automation, IaC, Policy as Code, and governance automation frameworks such as Terraform and Ansible
Benefits:
- Comprehensive medical plan options, including plans with Health Savings Accounts
- Dental plan options
- Vision plan
- 401(k) plan with pre- and post-tax contributions and company match
- Full-flex work weeks where possible
- Paid vacation, sick, personal, holiday, parental, military, bereavement, and jury duty leave
- Typically 15 days of paid leave per calendar year
- 10 paid holidays per year
- Up to 160 hours of paid family leave in a rolling 12-month period for eligible employees
- Short- and long-term disability benefits
- Life insurance
- Accidental death and dismemberment insurance
- Personal accident insurance
- Critical illness insurance
- Business travel and accident insurance
- AI-powered career tool identifying career steps and learning opportunities
- Internal mobility team
- Wellness packages
- Competitive pay
- Award-winning culture of innovation
- Military-friendly workplace
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