Senior Agentic AI Engineer

Job Summary:

The Senior Agentic AI Engineer is the operational owner of the Constituent Data Layer (CDL) and the safe, secure rollout of AI agents across CaterTrax® constituent surfaces.

Reporting to the Director, Enterprise Architecture as a member of the Data Layer group, this engineer manages the CDL schema, the agent registry, and the policy engine that governs which agents can access which data under which conditions, and instruments the data flywheel that returns outcomes from agent actions back into the layer.

The role partners with the Director of Strategic Solutions on Brief-to-agent translation, with the Director, Product and Solutions on engineering intake, with platform engineering on runtime, and with Finance on data flywheel ROI metrics. Without this role, agents would be built ad hoc across teams with no shared governance; this seat ensures they are not.

Job Description:

ESSENTIAL DUTIES AND RESPONSIBILITIES

CONSTITUENT DATA LAYER OWNERSHIP

• Manage the Constituent Data Layer schema, including versioning, integrity, and evolution as constituent surfaces expand.
• Own the agent registry: the authoritative record of every agent operating across CaterTrax surfaces.
• Build and operate the policy engine governing which agents can access which data under which conditions.
• Establish and maintain shared governance so agents are built on the CDL rather than ad hoc across teams.

AGENT DEVELOPMENT & SAFE ROLLOUT

• Design, build, and deploy AI agents across constituent surfaces on the shared platform substrate.
• Implement guardrails, evaluation harnesses, and monitoring for agent behavior in production.
• Define and operate the rollout process for new agents, including staged release, human oversight, and rollback.
• Lead incident response for agent behavior issues, including root-cause analysis and remediation.

DATA FLYWHEEL & MEASUREMENT

• Instrument the data flywheel that returns outcomes from agent actions back into the Constituent Data Layer.
• Partner with Finance to define and report data flywheel ROI metrics.
• Ensure agent telemetry supports both product improvement and executive decision-making.

CROSS-FUNCTIONAL PARTNERSHIP

• Partner with the Director of Strategic Solutions on Brief-to-agent translation, converting constituent problem framing into agent designs.
• Partner with the Director, Product and Solutions on engineering intake and sequencing.
• Partner with platform engineering on agent runtime, deployment, and operational readiness.

ENGINEERING EXCELLENCE

• Uphold engineering standards, code review practices, and documentation quality across all Data Layer work.
• Embed security and privacy by design into every agent and data-layer decision.

QUALIFICATIONS AND EXPERIENCE INCLUDES

EDUCATION

Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline required.

Master’s degree preferred.

EXPERIENCE

Required:

• 6+ years of professional software engineering experience, including 2+ years building LLM-based or AI-powered systems in production.
• Hands-on experience with retrieval-augmented generation (RAG), vector databases, and prompt/agent design patterns.
• Strong data modeling and API design skills, including schema governance in a shared-platform context.
• Experience implementing evaluation, monitoring, and guardrails for AI systems in production.
• Proficiency in Python and/or a modern backend language used in production services.

Preferred:

• Experience with agent orchestration frameworks, agent registries, or policy/authorization engines.
• Experience in foodservice technology, hospitality tech, or B2B SaaS platforms.
• Familiarity with responsible AI practices, AI governance frameworks, and data privacy regulations.

SKILLS AND COMPETENCY REQUIREMENTS

• Ownership: Treats the Constituent Data Layer as a product with constituents, not a project with tasks.
• Safety mindset: Designs for what agents must never do before optimizing what they can do.
• Pragmatic shipping: Delivers working, governed capability iteratively rather than perfect systems slowly.
• Cross-functional translation: Moves fluently between constituent problem language and engineering design.
• Documentation discipline: Leaves every schema, agent, and policy legible to the next engineer.
• Curiosity: Tracks the rapidly evolving agentic AI landscape and applies it judiciously.

TECHNOLOGY SKILLS

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