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Manager Vector Pipeline Jobs (NOW HIRING)

Architect, Data AI

Durham, NC · On-site

$61.50 - $79.25/hr

... and manage vector database solutions (e.g., Pinecone, Weaviate, FAISS, Milvus) for embeddings, hybrid search, and RAG pipelines. • Leverage advanced statistical and data science techniques to ...

Manage enterprise data and high-dimensional vector embeddings within PostgreSQL , ensuring efficient retrieval for RAG (Retrieval-Augmented Generation) pipelines. * LLM Integration & Optimization:

Manage enterprise data and high-dimensional vector embeddings within PostgreSQL , ensuring efficient retrieval for RAG (Retrieval-Augmented Generation) pipelines. * LLM Integration & Optimization:

Manage enterprise data and high-dimensional vector embeddings within PostgreSQL , ensuring efficient retrieval for RAG (Retrieval-Augmented Generation) pipelines. * LLM Integration & Optimization:

Manage enterprise data and high-dimensional vector embeddings within PostgreSQL , ensuring efficient retrieval for RAG (Retrieval-Augmented Generation) pipelines. * LLM Integration & Optimization:

Data Platform Engineer

$117K - $140K/yr

About Vector Health Vector Health helps rural hospitals unlock financial aid for their patients by ... Your focus will be on building pipelines that ingest and structure hospital data, ensuring quality ...

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How much do manager vector pipeline jobs pay per hour?

As of Jul 8, 2026, the average hourly pay for manager vector pipeline in the United States is $21.89, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $21.15 per hour, depending on experience, location, and employer.
What cities are hiring for Manager Vector Pipeline jobs? Cities with the most Manager Vector Pipeline job openings:
What are the most commonly searched types of Vector Pipeline jobs? The most popular types of Vector Pipeline jobs are:
What states have the most Manager Vector Pipeline jobs? States with the most job openings for Manager Vector Pipeline jobs include:
Infographic showing various Manager Vector Pipeline job openings in the United States as of July 2026, with employment types broken down into 85% Full Time, 13% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $45,538 per year, or $21.9 per hour.
Architect, Data AI

Architect, Data AI

JAGGAER

Durham, NC • On-site

$61.50 - $79.25/hr

Full-time

Re-posted 20 days ago


Job description

Job Summary:
JAGGAER provides an intelligent Source-to-Pay and Supplier Collaboration Platform that empowers organizations to manage and automate complex processes. They are hiring an Architect, Data AI to lead the AI/ML initiatives, architect production-grade AI systems, and collaborate with product and engineering teams to deliver measurable AI outcomes.
Responsibilities:
• Set and own the AI/ML technical strategy for the platform — from model architecture to evaluation, deployment, and monitoring — and rally engineering and product leadership around it.
• Design, develop, and deploy machine learning models for prediction, classification, clustering, and time-series analysis.
• Develop Generative AI and LLM-powered solutions, including RAG pipelines for knowledge retrieval and contextual responses.
• Build and optimize Agentic AI systems capable of multi-step reasoning, tool orchestration, and autonomous workflows.
• Architect and manage vector database solutions (e.g., Pinecone, Weaviate, FAISS, Milvus) for embeddings, hybrid search, and RAG pipelines.
• Leverage advanced statistical and data science techniques to extract actionable insights from structured and unstructured datasets.
• Implement and scale AI/ML pipelines using AWS services (SageMaker, Lambda, API Gateway, Bedrock, S3, EKS).
• Set the technical bar for the data science / ML function — design reviews, code and model reviews, technical standards, and upskilling peers and engineers around AI/ML best practices.
• Partner with business, product, and engineering leaders to translate procurement and supply chain problems into measurable AI/ML solutions.
• Write efficient, modular, and maintainable Python code for modeling, data processing, and deployment.
• Use advanced SQL for querying, transforming, and analyzing large relational datasets.
• Establish standards for model evaluation, observability, and responsible AI — including documentation, reproducibility, and guardrails for LLM and agent systems.
Qualifications:
Required:
• 14–15 years of experience in data science / applied ML, including 3–4 years building production Generative AI and Agentic AI systems with LangChain, LangGraph, and LangFlow.
• Track record of technical leadership without direct reports — setting architecture, driving cross-team alignment, and shipping AI/ML into production at enterprise scale.
• Proven expertise in conventional ML techniques: regression, classification, clustering, time-series forecasting, and predictive modeling.
• Proven track record of developing and deploying Generative AI, LLM-based, RAG-based, and Agentic AI solutions.
• Experience with LangChain, LangGraph, LangFlow, or similar agent frameworks.
• Strong proficiency in Python for machine learning, data manipulation, and deployment.
• Advanced SQL skills for working with large relational datasets, including hands-on experience with Snowflake (warehousing, performance tuning, and integration with ML/AI pipelines).
• Hands-on experience with AWS services (SageMaker, Bedrock, Lambda, EKS, API Gateway, S3).
• Hands-on experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) as a core component of RAG pipelines.
• Familiarity with data engineering principles and cloud-based data pipelines.
• Strong judgment translating ambiguous business problems into concrete AI/ML solutions — and the discipline to know when ML is the wrong tool.
Preferred:
• Exposure to Model Context Protocol (MCP) for orchestrating AI applications.
• Background in MLOps/CI-CD pipelines for deploying and monitoring ML models at scale.
• Familiarity with deep learning frameworks (TensorFlow, PyTorch) for advanced modeling.
Company:
Jaggaer is SaaS that manages spending, suppliers, contracts, sourcing, shopping, inventory and accounts payable of businesses. Founded in 1995, the company is headquartered in Cary, USA, with a team of 1001-5000 employees. The company is currently Late Stage.