Senior Agentic AI Engineer
Senior Agentic AI Engineer
Posted today
SENIORITY
Lead
SALARY
$140k
About the role
- 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.
- 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. 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 SKILLSThe 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.
- Agent orchestration frameworks, function/tool calling, and multi-agent patterns.
- 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.
- Containerization and orchestration: Docker and Kubernetes.
- Serverless and event-driven architecture patterns. DATA & ANALYTICS
- SQL, relational, and vector databases.
- Data pipeline and transformation tooling.
- Schema design, data contracts, and data governance practices. SOFTWARE ENGINEERING & DEVOPS
- Source control and collaboration: Git, GitHub, or GitLab, including PR workflows and code review practices.
- CI/CD pipeline platforms: GitHub, Azure DevOps.
- API design and management; identity and access patterns (OAuth 2.0, SSO/SAML).
- Agile and project management tooling: Jira, Confluence (Atlassian suite experience preferred). PRODUCTIVITY & COLLABORATION
- Microsoft 365 suite: Teams, SharePoint, Excel, and PowerPoint.
- AI productivity tools: Microsoft Copilot, Anthropic Claude, or similar for personal and team enablement. PHYSICAL DEMANDSWhile performing the duties of this job, the employee is regularly required to sit; use hands to operate a computer, copier, fax or other office equipment. The employee must occasionally lift and/or move up to 15 pounds. WORK ENVIRONMENTAssumes a hybrid work environment.
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