CareerPlanGet AI match score →
💼 Full-time🗓 2026-06-25

Core

Building agentic workflows, data-aware AI systems, and analytical pipelines to help franchise operators understand business operations and take action.

Role type

Senior IC AI Engineer (Agentic Systems)

Builds

Production-grade agentic workflows, conversational query interfaces, and data pipelines for franchise operators

Domain

Franchise operations, AI, Data Engineering

Deliverable

production ML models | product features

Required skills

Python, agentic systems (LangChain, LangGraph, CrewAI, ADK), MongoDB, SQL, ReAct agents, retrieval pipelines, embeddings, vector stores, AWS deployment, observability (Langfuse, LangSmith)

Preferred skills

BI-style data models, dashboarding, Snowflake, SQL warehouses, conversational query layers, semantic search

Technologies

Python, LangChain, LangGraph, MCP, MongoDB, SQL, AWS, Langfuse, LangSmith, Vector Stores

Responsibilities

Build conversational query interfaces and agentic workflows over data; Design and ship MCP servers to expose warehouse data; Build ReAct agents that reason over multi-source data; Deploy and monitor AI systems on AWS

Seniority

Senior, hands-on IC

Rewrite
## About the Role We're looking for an AI engineer to work on the intelligence layer of our platform — building agentic workflows, data-aware AI systems, and analytical pipelines that help franchise operators understand what's happening in their business and take the right action. You'll work across data, AI, and backend pipelines on AWS, and ship production-grade systems end to end. ## Responsibilities - Build conversational query interfaces and agentic workflows over MongoDB and SQL data to surface operational insights - Design and ship MCP servers to expose warehouse data as clean, agent-consumable interfaces - Build ReAct agents that reason over multi-source data and take multi-step actions - Deploy and monitor AI systems on AWS, collaborating with backend and product to ship end-to-end pipelines ## Requirements ### Must Have - 3–5 years of ML experience with Python, including 1+ years shipping agentic systems in production (LangChain, LangGraph, CrewAI, ADK or similar) - Solid understanding of MongoDB and SQL data systems, including KPI and analytics-style data - Experience building or consuming MCP servers and ReAct agents in production - Hands-on experience with retrieval pipelines, embeddings, vector stores, and traditional ML/NLP - AWS deployment and observability experience (Langfuse or LangSmith) ### Nice to Have - Experience with BI-style data models or dashboarding systems - Familiarity with Snowflake or SQL warehouses - Prior work building conversational query layers or semantic search systems ## Tech Stack - Python - LangChain - LangGraph - MCP - MongoDB - SQL - AWS - Langfuse / LangSmith - Vector Stores
Sourced via wellfound · Listed on CareerPlan, which tracks 70,000+ jobs from 20+ sources.
Apply on Wellfound ↗