Director, AI Assisted Software Engineering

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director, AI Assisted Software Engineering based in the United States. This is a senior engineering leadership role focused on building and scaling an enterprise-wide AI-assisted software development capability. You will define the strategy, operating model, technical foundations, and best practices that enable teams to use modern AI throughout the software development lifecycle. The role combines engineering leadership, architecture, AI development expertise, organizational change, and go-to-market thinking. You will evaluate and operationalize AI-enabled development tools, establish responsible adoption practices, and help engineers improve productivity and delivery quality. The position offers significant influence across distributed, cross-functional teams and emerging technology initiatives. It is well suited to an experienced engineering leader who enjoys building new capabilities from the ground up and turning emerging technologies into scalable practices.

Accountabilities

• cluding LLM-based solutions and agentic development technologies.
• Establish development standards covering prompt engineering, code-generation workflows, validation, security, quality, architecture, and responsible AI usage.
• Assess organizational AI-development maturity and develop roadmaps, capability models, adoption strategies, and new operating models to improve delivery.
• Lead the development and scaling of engineering teams, including hiring, coaching, mentoring, capability development, and adoption of AI-assisted engineering practices.
• Create developer education programs, playbooks, communities of practice, and other enablement initiatives that support organization-wide transformation.
• Serve as an internal subject-matter expert on how AI impacts software architecture, design patterns, quality models, engineering workflows, and delivery processes.
• Drive technical vision, architecture standards, and execution across complex, multi-team software programs and full product lifecycles.
• Establish and improve engineering practices including CI/CD, DevSecOps, test-driven and behavior-driven development, automation, and quality engineering.
• Contribute hands-on technical expertise across full-stack development, APIs, web services, modern frameworks, operating systems, cloud platforms, and scalable architecture.
• Use LLM-based frameworks and retrieval-augmented generation (RAG) to support software delivery and AI-enabled engineering workflows.
• Track and communicate the business value and ROI associated with AI adoption, automation, and productivity improvements.
• Partner with senior stakeholders to translate technical concepts into practical strategies, influence organizational decisions, and support adoption of emerging technologies.
• Help transform internally developed capabilities into scalable customer-facing solutions or services where appropriate.
• Stay current with developments in AI, software engineering, architecture, and emerging technologies, incorporating relevant innovations into organizational strategy.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience.
• 5+ years of progressive software engineering experience with 3–5+ years in technical leadership; 10+ years of software engineering experience is preferred.
• Demonstrated experience building and leading high-performing engineering teams, including coaching, mentoring, hiring, and capability development.
• Strong practical understanding of AI-assisted development workflows, including prompt engineering, code-generation improvement loops, safety and quality validation, architectural implications, and AI/agentic automation ROI.
• Direct experience evaluating, selecting, and operationalizing AI-enabled development tools such as GitHub Copilot, Azure AI, OpenAI models, Claude Code, or comparable technologies.
• Hands-on experience with LLM-based frameworks and retrieval-augmented generation (RAG) in software delivery environments.
• Proven ability to assess AI-development maturity and establish adoption roadmaps, capability models, operating models, and organizational change initiatives.
• Strong experience defining technical vision and architecture standards across complex, multi-team programs.
• Experience leading full software deve…