AI Engineer

Staffing Spot, Inc.; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Staffing Spot, Inc. seeks an experienced AI Machine Learning Engineer to design, develop, and deploy enterprise‑grade AI solutions.

You will build intelligent agents, RAG architectures, and AI‑powered workflow automation to improve operational efficiency and business value. The role requires hands‑on experience with LLMs, prompt engineering, multi‑agent systems, and cloud‑native deployment across Azure, AWS, or GCP.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, ML, Software Engineering, or related field.
• 10+ years of experience in AI, ML, or Software Engineering.
• Minimum 5+ years of hands‑on experience building and deploying Agentic AI applications in enterprise environments.
• Proven experience designing AI agents and contributing to agent architecture.
• Strong experience in workflow automation and operations‑focused AI solutions.
• Strong programming skills in Python and SQL.
• Hands‑on experience with: Agentic AI, LLMs, RAG, Prompt Engineering, Multi‑Agent Systems.
• Experience with AI frameworks including: LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI, Azure OpenAI.
• Experience with vector databases such as: Pinecone, FAISS, ChromaDB.
• Experience developing REST APIs.
• Experience building cloud‑native AI applications on Azure, AWS, or GCP.
• Familiarity with Docker, Kubernetes, Git, and CI/CD pipelines.
• Excellent analytical, communication, and problem‑solving skills.

Responsibilities

• Design, develop, and deploy enterprise‑scale Agentic AI solutions.
• Build intelligent AI agents and contribute to agent architecture and orchestration frameworks.
• Develop AI‑powered workflow automation solutions for business operations.
• Design and implement Retrieval‑Augmented Generation (RAG) architectures.
• Build and optimize Large Language Model (LLM) applications using prompt engineering and multi‑agent systems.
• Translate business requirements into scalable AI solutions and production‑ready applications.
• Collaborate with cross‑functional teams including Operations, Product, Business Analysts, and Software Engineering.
• Develop and maintain REST APIs and cloud‑native AI applications.
• Integrate AI applications with enterprise systems and operational workflows.
• Optimize AI models for performance, scalability, reliability, and security.
• Follow software engineering best practices including CI/CD, version control, testing, and containerization.

Skills

Agentic AI

LLMs

Prompt Engineering

Multi-Agent Systems

Automation

REST APIs

Cloud-native AI

Python

SQL

CI/CD

Docker

Kubernetes

Git

Education

Bachelor’s or Master’s degree in Computer Science, AI, ML, Software Engineering, or related field

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

OpenAI

Azure OpenAI

Pinecone

FAISS

ChromaDB

Job description

Position Overview

We are seeking an experienced AI Machine Learning Engineer to design, develop, and deploy enterprise-grade Agentic AI solutions. The ideal candidate will have a strong background in Artificial Intelligence, Machine Learning, and Software Engineering, with hands‑on experience building AI agents, workflow automation solutions, and production‑ready Generative AI applications. This role requires close collaboration with business stakeholders, operations teams, and technology partners to deliver scalable AI solutions that improve operational efficiency and drive business value.

Key Responsibilities

• Design, develop, and deploy enterprise‑scale Agentic AI solutions.
• Build intelligent AI agents and contribute to agent architecture and orchestration frameworks.
• Develop AI‑powered workflow automation solutions for business operations.
• Design and implement Retrieval‑Augmented Generation (RAG) architectures.
• Build and optimize Large Language Model (LLM) applications using prompt engineering and multi‑agent systems.
• Translate business requirements into scalable AI solutions and production‑ready applications.
• Collaborate with cross‑functional teams including Operations, Product, Business Analysts, and Software Engineering.
• Develop and maintain REST APIs and cloud‑native AI applications.
• Integrate AI applications with enterprise systems and operational workflows.
• Optimize AI models for performance, scalability, reliability, and security.
• Follow software engineering best practices including CI/CD, version control, testing, and containerization.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
• 10+ years of experience in AI, Machine Learning, or Software Engineering.
• Minimum 5+ years of hands‑on experience building and deploying Agentic AI applications in enterprise environments.
• Proven experience designing AI agents and contributing to agent architecture.
• Strong experience in workflow automation and operations‑focused AI solutions.
• Strong programming skills in Python and SQL.
• Hands‑on experience with:
  • Agentic AI
  • Large Language Models (LLMs)
  • Retrieval‑Augmented Generation (RAG)
  • Prompt Engineering
  • Multi‑Agent Systems
• Experience with AI frameworks including:
  • LangChain
  • LangGraph
  • LlamaIndex
  • Semantic Kernel
  • OpenAI
  • Azure OpenAI
• Experience with vector databases such as:
  • Pinecone
  • FAISS
  • ChromaDB
• Experience developing REST APIs.
• Experience building cloud‑native AI applications on Azure, AWS, or GCP.
• Familiarity with Docker, Kubernetes, Git, and CI/CD pipelines.
• Excellent analytical, communication, and problem‑solving skills.
• Skills: automation,semantic kernel,langgraph,openai and azure openai,artificial intelligence,machine learning,llamaindex