Director of Engineering

New American Funding

5h•$170,000 - $190,000•Remote

About The Position

The Director of Engineering, is responsible for leading and evolving NAF’s artificial intelligence (AI) and data-driven engineering capabilities. This role focuses on translating AI strategy into scalable, secure, and high-quality platforms that deliver measurable business value. The Director partners closely with Product, Data, Architecture, and senior leadership to guide AI-first technical direction, ensure predictable delivery, and develop high-performing engineering leaders and teams. This role blends hands-on technical leadership with organizational ownership, serving as the accountable leader for AI engineering outcomes across the enterprise.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline.
10+ years of experience in software engineering, including data-intensive or AI-adjacent systems.
5+ years of experience leading engineering teams and managers.
Demonstrated experience delivering AI, machine learning, or data-driven platforms in production environments.
Strong understanding of AI/ML system architecture, data pipelines, and model lifecycle management.
Experience guiding adoption of generative AI, predictive models, or intelligent automation.
Proven ability to lead distributed or offshore teams.
Excellent interpersonal, written, and verbal communication skills.
Strong troubleshooting skills with the ability to assess complex systems and architectures quickly.
Experience with modern backend and frontend technologies (e.g., .NET/C#, Java, Python, JavaScript/TypeScript).
Experience with cloud platforms such as Azure, GCP, and/or AWS, including scalable AI workloads.
Familiarity with DevOps and MLOps pipelines, CI/CD practices, and automated testing strategies.
Knowledge of security, privacy, and compliance considerations for AI and data platforms.
Ability to stay current with evolving AI technologies and apply them pragmatically.

Nice To Haves

Experience in highly regulated industries (e.g., financial services or fintech) preferred.
Demonstrated success scaling teams, platforms, and AI capabilities in growth environments.
Familiarity with Message Based Software Architecture is a plus.
Domain Driven Design (DDD) knowledge or experience
Knowledge of Back End and Front-End application structures
Experience with Persistent storage, RDBMS, Blob, NoSQL, is a plus
3rd Party Saas Integration experience is a plus

Responsibilities

Lead, mentor, and scale AI-focused engineering teams, including engineering managers and senior engineers.
Establish and track OKRs, engineering metrics, and quality standards for AI initiatives.
Foster a culture of innovation, accountability, and continuous improvement.
Serve as a point of contact for offshore or distributed AI team hiring and collaboration.
Partner closely with Product and Data leaders to translate AI capabilities into measurable business outcomes.
Remove organizational and technical impediments that block execution.
Manage engineering budgets, capacity planning, and resource allocation for AI initiatives.
Support performance management, career development, and succession planning for engineering leaders.
Be present and engaged with teams, providing guidance on vision, execution, and organizational effectiveness.
Define and execute AI engineering strategy aligned with business objectives and product roadmaps.
Drive adoption of modern AI architectures, including machine learning systems, generative AI, and intelligent automation.
Oversee the design and evolution of scalable, secure, and reliable AI platforms and services.
Ensure predictable, high-quality delivery of AI features, platforms, and enhancements.
Identify, communicate, and mitigate technical, delivery, operational, and security risks.
Collaborate closely with Architects to evaluate, introduce, and adopt new tools, frameworks, and platforms.
Champion modern engineering practices, including CI/CD, MLOps, automated testing, and observability.
Present new AI technologies, tools, and approaches for evaluation and adoption.
Ensure responsible, secure, and compliant use of AI technologies.