C
Senior Agentic AI Engineer
CaterTrax
5 hours ago
Full-time
On-site
Rochester, New York, United States
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. On-site work is expected at our newly renovated office in The Village Gate.
CONSTITUENT DATA LAYER OWNERSHIP ● Manage the Constituent Data Layer schema, including versioning, integrity, and evolution as constituent surfaces expand. ● 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. ● 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. ● CROSS-FUNCTIONAL PARTNERSHIP ● 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.
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.
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.
Treats the Constituent Data Layer as a product with constituents, not a project with tasks. ● Pragmatic shipping: Moves fluently between constituent problem language and engineering design. ● Leaves every schema, agent, and policy legible to the next engineer. ● Tracks the rapidly evolving agentic AI landscape and applies it judiciously.
The Senior Agentic AI Engineer is expected to bring deep hands-on proficiency across the following technology domains.
AI & MACHINE LEARNING PLATFORMS ● Large language model (LLM) platforms: OpenAI / Azure OpenAI, Anthropic Claude, AWS Bedrock, or equivalent. ● Retrieval-augmented generation (RAG) architecture and vector database platforms. ● AI ops tooling for model monitoring, versioning, drift detection, and deployment pipelines. CLOUD & INFRASTRUCTURE ● Cloud platforms: proficiency in Microsoft Azure, with fluency across AWS and Google Cloud. ● DATA & ANALYTICS ● SQL, relational, and vector databases. ● Data pipeline and transformation tooling. ● Schema design, data contracts, and data governance practices. SOFTWARE ENGINEERING & DEVOPS ● CI/CD pipeline platforms: GitHub, Azure DevOps. ● Agile and project management tooling: Microsoft 365 suite: Teams, SharePoint, Excel, and PowerPoint. ● AI productivity tools: Microsoft Copilot, Anthropic Claude, or similar for personal and team enablement.
use hands to operate a computer, copier, fax or other office equipment. Assumes a hybrid work environment. TRAVEL Up to 10%, Domestic (as required)
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. On-site work is expected at our newly renovated office in The Village Gate.
CONSTITUENT DATA LAYER OWNERSHIP ● Manage the Constituent Data Layer schema, including versioning, integrity, and evolution as constituent surfaces expand. ● 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. ● 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. ● CROSS-FUNCTIONAL PARTNERSHIP ● 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.
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.
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.
Treats the Constituent Data Layer as a product with constituents, not a project with tasks. ● Pragmatic shipping: Moves fluently between constituent problem language and engineering design. ● Leaves every schema, agent, and policy legible to the next engineer. ● Tracks the rapidly evolving agentic AI landscape and applies it judiciously.
The Senior Agentic AI Engineer is expected to bring deep hands-on proficiency across the following technology domains.
AI & MACHINE LEARNING PLATFORMS ● Large language model (LLM) platforms: OpenAI / Azure OpenAI, Anthropic Claude, AWS Bedrock, or equivalent. ● Retrieval-augmented generation (RAG) architecture and vector database platforms. ● AI ops tooling for model monitoring, versioning, drift detection, and deployment pipelines. CLOUD & INFRASTRUCTURE ● Cloud platforms: proficiency in Microsoft Azure, with fluency across AWS and Google Cloud. ● DATA & ANALYTICS ● SQL, relational, and vector databases. ● Data pipeline and transformation tooling. ● Schema design, data contracts, and data governance practices. SOFTWARE ENGINEERING & DEVOPS ● CI/CD pipeline platforms: GitHub, Azure DevOps. ● Agile and project management tooling: Microsoft 365 suite: Teams, SharePoint, Excel, and PowerPoint. ● AI productivity tools: Microsoft Copilot, Anthropic Claude, or similar for personal and team enablement.
use hands to operate a computer, copier, fax or other office equipment. Assumes a hybrid work environment. TRAVEL Up to 10%, Domestic (as required)