AI Platform Lead: RAG, Knowledge Graphs & Production ML

Jobgether; United States; On-site; USD 151,000 - 242,000; Full time

Job summary

Jobgether is seeking an AI/ML Lead in the United States to build and scale internal AI capabilities. As the first AI engineer on the team, you will implement production-grade AI solutions focused on personalized member experiences using RAG, knowledge graphs, and recommender systems.

You will own data and retrieval pipelines, integrate large language models, and establish robust engineering practices for secure and scalable AI systems, collaborating across architecture, product, data, security,

Qualifications

• Bachelor's degree in a technical field or equivalent professional experience.
• 8+ years of professional software/data experience with 2+ years building/operating production AI/ML solutions.
• Experience delivering enterprise-scale AI systems, preferably in cloud environments like Azure.

Responsibilities

• Architect, build, and operate production AI solutions with a focus on a personalized member experience using RAG, knowledge graphs, and recommendations.
• Lead AI platform engineering, including AI components, embeddings, retrieval pipelines, and LLM-driven apps.
• Define vendor engagement criteria, validate production readiness, and transition vendor components to internal ownership.

Skills

Python

LLM integration

RAG systems

MLOps

Data pipelines

Graph databases

Team leadership

Education

Bachelor's degree

Tools

Azure DevOps

GitHub Actions

Docker

Kubernetes

Azure Data Factory

LangChain

Job description

Jobgether is seeking an AI/ML Lead in the United States to build and scale internal AI capabilities. As the first AI engineer on the team, you will implement production-grade AI solutions focused on personalized member experiences using RAG, knowledge graphs, and recommender systems.

You will own data and retrieval pipelines, integrate large language models, and establish robust engineering practices for secure and scalable AI systems, collaborating across architecture, product, data, security,