Senior Agentic AI Engineer

CaterTrax•Rochester, NY

2d•$140,000 - $170,000•Hybrid

About The Position

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. This role manages the CDL schema, the agent registry, and the policy engine that governs agent access to data, and instruments the data flywheel that returns outcomes from agent actions back into the layer. The role partners with various directors and teams to ensure agents are built with shared governance and not ad hoc across teams.

Requirements

Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline 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.
Proficiency in Microsoft Azure, with fluency across AWS and Google Cloud.
Experience with containerization and orchestration: Docker and Kubernetes.
Experience with serverless and event-driven architecture patterns.
Experience with SQL, relational, and vector databases.
Experience with data pipeline and transformation tooling.
Experience with schema design, data contracts, and data governance practices.
Experience with source control and collaboration: Git, GitHub, or GitLab, including PR workflows and code review practices.
Experience with CI/CD pipeline platforms: GitHub, Azure DevOps.
Experience with API design and management; identity and access patterns (OAuth 2.0, SSO/SAML).
Experience with Agile and project management tooling: Jira, Confluence (Atlassian suite experience preferred).
Experience with Microsoft 365 suite: Teams, SharePoint, Excel, and PowerPoint.
Experience with AI productivity tools: Microsoft Copilot, Anthropic Claude, or similar for personal and team enablement.

Nice To Haves

Master's degree 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.
Experience with Large language model (LLM) platforms: OpenAI / Azure OpenAI, Anthropic Claude, AWS Bedrock, or equivalent.
Experience with agent orchestration frameworks, function/tool calling, and multi-agent patterns.
Experience with Retrieval-augmented generation (RAG) architecture and vector database platforms.
Experience with AI ops tooling for model monitoring, versioning, drift detection, and deployment pipelines.

Responsibilities

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.
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.
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.
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.
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.