This is a principal-level technical leadership role responsible for setting the direction of a large-scale agentic AI program. You’ll provide technical oversight across multiple AI workstreams, from problem framing and architecture through evaluation, deployment, and production operations. The role combines deep hands-on expertise in data science and AI/ML with program-wide architectural leadership and strategic decision-making. You’ll partner with executives and senior stakeholders to shape the AI roadmap and make high-impact decisions around technology, risk, quality, and delivery. You’ll establish standards for agentic systems, model evaluation, MLOps, reliability, security, and responsible AI across a large delivery organization. The environment is fast-moving and highly collaborative, with production AI expected to move from concept to deployment in approximately 30–45 days. This is an opportunity to shape not only sophisticated AI solutions, but also the technical practices and leadership culture that determine how agentic AI scales.
Provide technical oversight across all agentic AI workstreams, guiding initiatives from problem definition and architecture through evaluation, deployment, and ongoing operation.
Define the technical strategy and reference architecture for agentic AI systems, including multi-agent orchestration, tool and function calling, RAG, vector databases, embeddings, and streaming LLM responses.
Coordinate technical delivery across multiple teams and workstreams, identifying dependencies, resolving blockers, managing technical risk, and maintaining quality and velocity.
Establish standards for model development, experimentation, evaluation, and the transition from research concepts to reliable production systems.
Design and champion rigorous evaluation frameworks covering model and agent quality, safety, hallucination, cost, latency, and other meaningful performance indicators.
Guide the development of scalable ML platforms, pipelines, event-driven architectures, and workflow orchestration systems supporting asynchronous AI operations.
Ensure deployed AI systems meet high standards for reliability, security, scalability, observability, monitoring, and production debugging.
Serve as the senior technical representative for the AI/ML program with executive and client stakeholders, communicating progress, risks, trade-offs, and technical decisions clearly.
Partner with executive leadership to define and evolve the AI roadmap, contributing as a strategic technical peer on high-impact decisions.
Translate complex AI and data science concepts into actionable decisions for executives, engineers, product teams, and business stakeholders.
Align data science, engineering, product, and business teams around shared priorities, technical standards, and measurable outcomes.
Lead and influence a large, multi-team delivery organization while establishing expectations for technical excellence across workstreams.
Review technical work across teams, provide direct and constructive feedback, and raise the quality of architecture, implementation, and delivery.
Mentor technical leads and senior practitioners, helping develop the next generation of AI and technical leaders.
Own high-stakes technical decisions that affect the broader program, balancing innovation, delivery speed, reliability, and risk.
Continuously evolve the technical vision and define how agentic AI engineering and data science practices should mature across the program.
Use modern AI-assisted development tools and workflows to improve productivity, engineering quality, and delivery speed.