Director, Applied AI Engineering

About the Role

As a Director, Applied AI Engineering, you will shape and own the engineering strategy and technical direction for your service line. You will translate business objectives into engineering strategy, map business capabilities to the enterprise technology landscape, and define how GenAI and agentic capabilities are built directly into the products we deliver. Your leadership will be pivotal in delivering tangible value across the service line's product and AI investments, aligning technical solutions with business and technology strategy, and advancing Applied AI engineering across the organization.

Responsibilities

• Strategic Vision and Alignment: Define, communicate, and refine the engineering strategy for the service line, aligning with business and technology objectives. Collaborate with diverse stakeholders, including executives, product, engineering, and infrastructure teams.
• Advocacy and Technology Roadmap: Champion and execute the integrated Applied AI engineering strategy, driving simplification, scalability, and efficiency. Rationalize the technology landscape and ensure alignment with objectives, KPIs, and progress.
• Craft Mastery and Objectives Realization: Define and drive KPIs and non-functional requirements (NFRs) for system performance, scalability, security, and reliability. Establish and evolve reference architectures, standards, and best practices.
• Capability Evolution and Development: Mentor and develop engineers and emerging leaders, fostering a growth mindset and modern engineering behaviors. Lead by example through thought leadership and R&D collaborations.
• Iterative Value Delivery: Embrace an iterative approach to product engineering, ensuring each iteration delivers value and aligns with customer and business goals.
• Customer-Centric Problem Solving: Focus on solving critical customer challenges, minimizing technical complexity, and driving teams toward peak performance.
• Tech/Quality Risk Management: Establish enterprise reference architectures and coding standards to ensure robust, secure, and scalable solutions. Proactively identify and mitigate technical risks.
• Influential Communication: Drive decision-making through effective communication, crafting clear arguments and technical trade-offs.
• Organizational Engagement and Collaboration: Build collaborative relationships with stakeholders at all levels, co-creating momentum and value across the organization.

Qualifications

• Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline.
• 12+ years of full-stack software engineering experience with technologies such as Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, REST/SOAP/GraphQL, SSO/MFA, PyTorch, TensorFlow, LangChain, and LangGraph.
• 8+ years of experience architecting enterprise solutions on modern technology stacks (API Gateways, Message Brokers, Cloud-native engineering, etc.) and cloud platforms (Azure, AWS, GCP).
• 5+ years of experience building AI/ML and agentic applications, including LLM integration, RAG pipelines, and AI agent orchestration.
• 5+ years of experience establishing and leading enterprise engineering standards and mentoring large engineering teams.
• Experience with methodologies like XP, Lean, DevSecOps, SRE, and tools such as ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks.
• Ability to work in a local office at least 3 days per week and travel 10% on average.

Skills

• Excellent interpersonal and organizational skills, with the ability to handle complex projects and changing priorities.
• Deep expertise in modern Applied AI engineering and architecture practices.
• Strong leadership and mentoring abilities, with a focus on developing engineering talent.
• Ability to influence and drive decision-making across the organization.

The wage range for this role is $151,400 to $311,000, with the potential for a discretionary annual incentive program based on performance.