
- Top 5% of respondersAutomatisor is in the top 5% of companies in terms of response time to applications
- Responds within a dayBased on past data, Automatisor usually responds to incoming applications within a day
AI Engineer
- No equity
- |Remote ()
- |1 year of exp
- |Full Time
Remote only
Not Available
About the job
Automatisor offers facility intelligence for revenue teams at material handling automation providers. It does three things: Automatisor discovers facilities that show real signals of automation needs such as labor strain, broken processes or expansion plans. It qualifies facilities that are good fit for a specific solution backed by evidence. It hands teams a personalized outreach plan.
This allows revenue teams to build a pipeline of automation opportunities around accounts that are actually ready to buy, not ones that just look good on paper.
Our platform runs deep, continuous research across a warehouse's operations, labor, infrastructure, inventory, customers, and financials, sourced from 20+ vetted sources, cross-verified, and refreshed continuously. The result: qualified opportunities to pursue, complete with discovery prep and account context, so teams spend their time on the accounts that matter most.
We are looking for a full-time AI Engineer with a primary focus on developing Python modules for Generative AI applications, with hands-on experience building agentic systems. A strong understanding of AI workflows, prompt engineering, and model integration will be highly valued. The role will involve building reusable and efficient code modules, experimenting with AI-driven solutions, and integrating them into our core systems.
Specifically, we are looking for hands-on experience with:
Building agents that expose and consume MCP (Model Context Protocol) endpoints
Designing agents with a defined persona that can retrieve and reason over specific context pulled live from a database
Building agents that can serve both human-facing and API-driven requests/responses
Publishing agent outputs to a Streamlit app for interactive use
Tools & technologies we work with:
Agent frameworks / orchestration: LangGraph, Model Context Protocol (MCP) SDK
LLM & extraction: OpenAI APIs, prompt engineering, retrieval-augmented generation
API layer: FastAPI (or equivalent) for serving agents to both human and programmatic callers
Data & storage: Supabase / PostgreSQL, equivalent, vector databases
Frontend: React.js, Streamlit / equivalent
Experiment tracking & evaluation: LangSmith or equivalent (nice to have)
Version control & collaboration: Git/GitHub
What will you be doing?
Work with the founding team to build and evolve an AI-native, deep tech product
Build strong agentic systems to solve problems in hard industries like Logistics, Manufacturing & Supply Chain
Why should you apply?
You enjoy solving really complex problems in really challenging and hard industries.
You get a front seat in building an AI-native company alongside experienced builders and sellers.
You get to thrive in chaos, set processes and build systems.
You get a chance to become a founding member in the company.
Interview process
Take home Assignment & Review
Interview with Engineering
Interview with Business
Application details
We are looking for immediate, full-time joiners only.
We care more about what you can accomplish rather than what certificates you hold.
Please apply with your GitHub or equivalent profile showing relevant projects on gen AI/agentic systems. It must clearly show the code + preview of the project. Due to the volume of applications, applications without details of relevant projects will be auto-rejected.
About the company
- Top 5% of respondersAutomatisor is in the top 5% of companies in terms of response time to applications
- Responds within a dayBased on past data, Automatisor usually responds to incoming applications within a day
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