Associate Director, AI Engineering

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Establish the technical vision for AI Engineering, outlining architectural principles, engineering standards, delivery methodologies, and technical competencies.

• Take responsibility for the technical excellence of significant AI projects, particularly those characterized by architecture, scale, complexity, or delivery risks.

• Oversee multiple projects and technical initiatives, prioritizing tasks and guiding the team to successful execution.

• Design and assess production AI architectures, which encompass retrieval and knowledge layers, agentic pipelines, evaluations, and multilingual systems.

• Analyze trade-offs related to cost, latency, reliability, and scalability.

• Review code, prototype methodologies, address architectural challenges, and collaborate with engineers on complex issues.

• Conduct thorough design reviews and elevate engineering standards throughout the practice.

• Serve as the primary technical consultant to clients, including C-suite executives and architecture leaders.

• Ensure the technical quality of significant AI proposals, encompassing architectures, scopes, delivery models, team configurations, estimates, and commercial assumptions.

• Craft technical propositions, pinpoint opportunities, and steer investments in the AI Engineering practice.

• Mentor senior engineers and technical leads, fostering leadership depth and succession planning.

• Define the AI Engineering capability plan, including hiring priorities, skill development, team structure, and standards for senior technical talent.

⛳️ Requirements

• Minimum of 10 years of experience in AI, data, and software engineering.

• Over 3 years of experience leading engineering teams or a significant technical function within consulting or professional services.

• Experience extending beyond individual project leadership, with accountability for technical direction, engineering quality, or capabilities across multiple teams.

• Proven production Python experience with extensive codebases and API-driven systems operating reliably at scale.

• Recent hands-on experience in architecting and building production AI systems.

• Ability to discuss strategies related to retrieval, caching, context economics, serving constraints, evaluation, observability, and addressing practical failures.

• Strong systems thinking capabilities and the ability to navigate unfamiliar platforms and challenges.

• Experience leading intricate programs or multiple concurrent engineering streams with responsibility for technical direction, planning, resource allocation, risk management, and delivery outcomes.

• Sound judgment to personally intervene when necessary and effectively delegate while maintaining accountability for technical quality.

• Proven experience in mentoring senior engineers and technical leaders, enhancing engineering standards across an organization.

• Commercial insight to translate technical solutions into feasible scopes, team structures, estimates, and delivery strategies.

• Experience contributing to account growth, technical propositions, or go-to-market activities within a consulting environment.

• Confidence in engaging with senior clients and executives while retaining credibility with engineers at the code and architecture level.

• Capability to make challenging technical decisions, provide clarity amidst ambiguity, and take ownership of outcomes.

• Extensive experience with Databricks and Azure OpenAI.

• Nice to have: experience with ontologies, knowledge graphs, or semantic layers.

• Nice to have: delivery experience in the pharmaceutical or consumer packaged goods sectors.

• Nice to have: practical experience in designing systems compliant with EU AI Act requirements.

• Nice to have: experience with multilingual AI systems in a production setting.

• Nice to have: presence within the Databricks or Microsoft partner ecosystem.

• Nice to have: experience shaping go-to-market and commercial strategies for an AI Engineering practice.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Opportunities for professional development and advancement.

• Flexible work arrangements and a supportive work environment.

• Access to cutting-edge technology and tools.

• Collaborative and innovative team culture.