Description:

We are hiring a Founding Full-Stack AI/ML Engineer to help shape and scale the core of our agent-based AI platform.
You will work closely with the founder on roadmap execution, rapid prototyping, and evolving the product based on real-world use.
Your responsibilities will include building multi-agent systems with reasoning, autonomous action, and dynamic tool use.
You will implement Model Context Protocol (MCP) strategies to manage multi-source and multi-modal data.
The role involves integrating with third-party APIs such as Crunchbase, PitchBook, and CB Insights, as well as scraping APIs and data aggregators.
You will develop browser-based research agents using Playwright, Puppeteer, or similar frameworks.
Optimizing inference pipelines and agent orchestration workflows will be part of your duties.
You will lead architectural decisions and rapid prototyping cycles.
Experimenting with prompt chaining, tool calling, embeddings, and vector search will also be required.

Requirements:

Strong Python skills and hands-on experience with LangChain, LlamaIndex, or other agentic frameworks are essential.
Proven experience with multi-agent systems, tool calling, task planning, or context-aware systems is required.
Familiarity with MCP, RAG, and handling both structured and unstructured data is necessary.
Experience with browser automation tools such as Playwright, Selenium, or Puppeteer is needed.
A background in cloud deployment (GCP, AWS, etc.) and systems engineering is important.
The ideal candidate should be a self-starter with strong product intuition, speed, and adaptability.

You will gain hands-on experience with frameworks like AutoGen, CrewAI, OpenAgents, or ReAct.
The position offers the opportunity to blend structured and unstructured data into AI pipelines.
You will benefit from prior experience at an early-stage startup or as part of a technical founding team.