Senior Director of Agentic AI Engineering & Platform Architecture

Head of Agentic AI Engineering & Platform Architecture

 

Let’s be unstoppable together!

 

At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives. We have a global commitment to diversity, equity, and inclusion as we believe in the undeniable strength that diversity brings to our business, employees, clients, and communities. With us, you can always bring your full self to work. Join our inclusive, committed team to be a challenger, own outcomes, and stay curious together. Circana is proud to be Certified™ by Great Place To Work®. This prestigious award is based entirely on what current employees say about their experience working at Circana.

Learn more at www.circana.com.

 

What will you be doing?

We are seeking a Head of Agentic AI Engineering & Platform Architecture (Director or Sr Director) to lead the design, development, and scaling of our next-generation Agentic AI onboarding and analytics acceleration platform. This role combines principal-level architecture, hands-on engineering leadership, and client-facing technical ownership.

You will set the multi-year strategy for agentic automation, autonomous AI capabilities, metadata-driven ingestion, supervised learning reinforcement, and large-scale distributed processing. The ideal leader is deeply technical, product-oriented, and passionate about building real, production-grade multi-agent systems, not prototypes.

Success is measured by:

• Faster client onboarding
• Reduction in delivery rework
• Platform adoption across teams
• System reliability, scalability, and performance
• Engineering excellence and velocity

 

Job Responsibilities

1. Architecture & Platform Leadership

• Serve as the principal architect for Circana’s agentic AI platform, defining system architecture, integration patterns, and technical strategy.
• Lead design of multi-agent orchestration, context management, and distributed onboarding pipeline.
• Own evolution of Context Studio and metadata-driven automation frameworks.
• Ensure scalability, reliability, security, and cost efficiency across AI and data pipelines.
• Build Autonomous Agent Architecture that includes agent memory systems (working, long-term, semantic), self‑evaluation/reflection loops and reasoning‑improvement mechanisms, planning & task decomposition capabilities, multi-agent coordination, guardrails and governance policies.

1. Product & Roadmap Ownership

• Establish and maintain the multi-year platform roadmap, including next-generation automation agents, quality gate pipelines, and insight storytelling components.
• Must be product-oriented: focuses on durable, scalable solutions rather than one-off prototypes; ensures production readiness, user adoption, and alignment with long-term platform strategy.
• Must be product-oriented: focuses on durable, scalable solutions rather than one-off prototypes; ensures production readiness, user adoption, and alignment with long-term platform strategy.
• Partner closely with Product on prioritization, customer validation, UX integration, and cross-team adoption.

1. AI Governance, Security & Operational Controls

• Establish enterprise AI governance controls to ensure agentic systems operate within policy, regulatory, privacy, and data‑minimization boundaries, based on best‑practice governance patterns for agentic AI.
• Implement agent observability (decision logs, audit trails, monitoring dashboards) and behavioral tracking to maintain visibility into agent actions and prevent unintended data or system access. 3
• Integrate AI security measures to protect against misuse, privilege escalation, and unauthorized agent actions.
• Apply AIOps-based monitoring and LLMOps/MLOps operational practices (evaluation, drift monitoring, reproducibility, lifecycle automation) to ensure reliability, safety, and high‑quality outputs across all agent workflows

1. Hands-On Engineering Leadership

• Lead design and build-out of multi-agent automation, Spark-based ingestion,