AI Engineering Associate/Intern

Overview

On Site
Up to $80,000
Full Time
No Travel Required

Skills

Artificial Intelligence
Agentic AI

Job Details

Looking for: AI Engineering Associate/Intern
Job Type: Fulltime
Location: San Francisco, California

Is a Remote job?:false

Role Summary:

If you re excited about designing intelligent agents that can understand context, take initiative, and integrate seamlessly into enterprise workflows this is your chance to shape the future of AI in procurement.

Key Responsibilities:

AI Feature Development

  1. Agentic AI Feature Development

o Design, build, and deploy procurement-specific AI agents that can (eventually) take autonomous actions within the platform

o Plan, Design and Implement multi-step reasoning and goal-oriented planning using frameworks from any of the modern agent orchestration systems.

  1. Data Engineering & Infrastructure
  • Integrate agents with existing stack including GraphQL APIs (Hasura), Postgres DB, and Go-based backend services.
  • Build connectors for agents to interact with third-party systems (ERP, supplier databases, email integrations, etc.).
  • Develop retrieval-augmented generation (RAG) pipelines with vector databases for supplier and contract knowledge bases.
  1. Research & Experimentation
  • Prototype new use cases leveraging LLMs to improve procurement efficiency and decision-making.
  • Research tool-use patterns (e.g., agents invoking APIs or workflows) to blend reasoning with action.
  • Evaluate emerging AI tools, vector databases, and frameworks for product integration.
  • Partner with product managers and designers to define AI feature requirements and success metrics.
  • Collaborate with Go and TypeScript engineers to embed AI features into the platform.

Day-to-Day Work

A typical week might include:

  • Designing and experimenting with tool stack for Agentic platform
  • Prototyping an Contract Assistant Agent that could autonomously look at expiring contracts, draft renewals and send alert to relevant owners
  • Building a GraphQL action interface so agents can modify purchase requests or supplier data.
  • Writing production-grade Typescript or Go code for backend agent orchestration.
  • Experimenting with different reasoning strategies or LLM providers (OpenAI, Gemini )
  • Participating in sprint planning, reviews, and internal demos showcasing new AI capabilities.
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