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Vector Databases Jobs in Phoenix, AZ (NOW HIRING)

Troon Golf

AI Platform Architect

Scottsdale, AZ · On-site

Experience designing RAG pipelines and working with vector databases at production scale * Experience implementing agentic workflows or function-calling integrations with LLMs * Experience working ...

Intel

Analytics and AI Solution Architect

Phoenix, AZ

$188K - $265K/yr

... Vector databases in a Retrieval Augmented Generative AI architecture. - Apply Lambda architecture, database design, and data modeling to support scalable and efficient cloud-based applications ...

ClifyX

Java-Python-Senior Engineer

Phoenix, AZ · On-site

... vector databases, and observability systems for adaptive agent behavior. • Ensure reliability, performance, and maintainability through rigorous testing, type safety (mypy/pydantic), and production ...

VBeyond

Java-Python-Senior Engineer

Phoenix, AZ · On-site

... vector databases, and observability systems for adaptive agent behavior. • Ensure reliability, performance, and maintainability through rigorous testing, type safety (mypy/pydantic), and production ...

Honeywell

Sr. Advanced AI Software Engineer

Phoenix, AZ · On-site

$121K - $160K/yr

Embeddings, vector databases, and semantic search. * Programming & Software Engineering: Strong proficiency in Python (primary AI development language), Experience with at least one additional ...

Honeywell

Sr. Advanced AI Software Engineer

Phoenix, AZ

$121K - $160K/yr

Embeddings, vector databases, and semantic search. * Programming & Software Engineering: Strong proficiency in Python (primary AI development language), Experience with at least one additional ...

Honeywell

Sr. Advanced AI Software Engineer

Phoenix, AZ · On-site

$115K - $152K/yr

Embeddings, vector databases, and semantic search. * Programming & Software Engineering: Strong proficiency in Python (primary AI development language), Experience with at least one additional ...

Diverse Lynx

Java-Python-Senior Engineer

Phoenix, AZ · On-site

$100K - $120K/yr

... vector databases, and observability systems for adaptive agent behavior. • Ensure reliability, performance, and maintainability through rigorous testing, type safety (mypy/pydantic), and production ...

TriWest Healthcare

Sr AI Solution Architect

Phoenix, AZ · On-site

... vector databases, API gateways, and cloud inference endpoints • Demonstrated expertise in Privacy by Design architecture and automated PHI de-identification workflows • Experience developing ...

Arkhya Tech

GenAI Solutions Leader

Phoenix, AZ · On-site

Hands-on with GenAI and agentic AI (LLMs, diffusion models, RAG, tool use/agents); familiarity with OpenAI Azure, Hugging Face, LangChain/LangGraph, ADK, vector databases. Experience with MLOps ...

IntraEdge

Architect

Phoenix, AZ

$63 - $83/hr

... and Vector Databases • Expertise in one or more AI frameworks, such as LangChain. • Knowledge of AI concepts, such as machine learning, deep learning, natural language processing ...

Atos

SOFTWARE ENGINEER

Phoenix, AZ

Database Management: Implement vector databases for retrieval-augmented generation (RAG) workflows. Collaboration: Partner with Data Science teams to operationalize and scale Python-based prototypes ...

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Vector Databases information

What are vector databases?

Vector databases are specialized databases designed to store, manage, and search high-dimensional vector data, which is commonly generated from machine learning models, such as embeddings from natural language processing or image recognition. They enable efficient similarity search operations, such as finding the most similar items to a given query vector, which is essential for applications like recommendation systems, semantic search, and AI-powered search engines. Unlike traditional databases that handle structured or unstructured data, vector databases are optimized for fast and scalable similarity searches on large datasets of vectors.

What are some common challenges faced when working with vector databases, and how can they be addressed?

Professionals working with vector databases often encounter challenges such as efficiently scaling to handle large datasets, ensuring low-latency similarity searches, and integrating the database with machine learning pipelines. To address these, teams typically implement distributed architectures, fine-tune indexing strategies, and collaborate closely with data engineers and machine learning specialists. Staying updated with the latest developments in vector database technologies and maintaining clear communication with cross-functional teams are also key to overcoming these challenges.

What is the difference between Vector Databases vs Data Engineers?

AspectVector DatabasesData Engineers
Required SkillsDatabase management, data modeling, query optimizationData pipeline development, ETL processes, programming
Work EnvironmentData storage systems, AI/ML projects, cloud platformsData infrastructure, cloud environments, big data tools
Industry UsageAI, machine learning, recommendation systemsData integration, analytics, data architecture

While Vector Databases focus on storing and querying high-dimensional vector data for AI applications, Data Engineers build and maintain data pipelines and infrastructure to support data analysis and machine learning workflows. Both roles are essential in data-driven industries but serve different functions within the data ecosystem.

What are the key skills and qualifications needed to thrive as a Vector Database Engineer, and why are they important?

Success as a Vector Database Engineer requires a strong background in computer science, database management, and experience with machine learning or AI-driven data systems. Familiarity with vector database platforms (such as Pinecone, Milvus, or Weaviate), cloud infrastructure, and proficiency in languages like Python are typically expected. Strong problem-solving skills, effective communication, and the ability to work cross-functionally help engineers stand out. These competencies are vital to efficiently design, deploy, and maintain scalable vector search solutions that power modern AI applications.
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Vector Databases jobs near you
AI Platform Architect

AI Platform Architect

Troon Golf

Scottsdale, AZ • On-site

Other

Posted 19 days ago

Troon rating

6.2

Company rating: 6.2 out of 10

Based on 119 frontline employees who took The Breakroom Quiz

16th of 27 rated golf clubs

Job description

Troon's Corporate office, located in Scottsdale, AZ, is pleased to announce an excellent career opportunity for an AI Platform Architect! We are seeking a highly motivated individual who is eager to learn, contribute, and advance their career within a rapidly growing organization. The ideal candidate will bring a strong commitment to professional development and a desire to succeed in a dynamic corporate environment.
The AI Platform Architect designs and implements the architecture that connects Troon's data platform to AI-enabled applications, including retrieval-augmented generation (RAG) services, document and content pipelines, agent-to-data interfaces, and AI workflow orchestration. Builds reusable platform components and patterns that enable AI use cases to be delivered consistently, reliably, and at scale across the organization. Serves as the technical authority on how AI systems consume Troon's data and interact with operational systems of record.
Key Responsibilities:

  • Design and build reusable architectural components for AI-enabled solutions, including retrieval pipelines, knowledge bases, document parsing, validation engines, content and KPI libraries, and workflow orchestrators that accelerate delivery across use cases
  • Define how AI agents and applications interact with Troon's data platform, including retrieval scopes, function-calling schemas, and write-back patterns, and implement integration with systems of record (e.g., Dynamics F&O, Dynamics CE, Premier POS) to ensure data quality, freshness, and auditability
  • Design semantic data models, embeddings strategies, and vector storage approaches that make Troon's data consumable by large language models
  • Establish technical patterns for AI implementation, including prompt design, output validation, evaluation harnesses, and feedback capture loops
  • Lead technical design reviews for AI use cases and ensure architectural alignment with the broader Azure and Microsoft Fabric platform
  • Partner with the Sr. Data Platform Architect on the underlying data foundation and with full stack developers on application-layer integration
  • Optimize performance, cost, and reliability across AI workloads, including model selection, caching, and retrieval efficiency
Required Qualifications:
  • 7+ years of experience in software architecture, data engineering, or platform engineering
  • 2+ years of hands-on experience designing AI/ML or LLM-powered applications
  • Proven experience integrating AI systems with enterprise data platforms and operational systems
Preferred Qualifications:
  • Experience designing RAG pipelines and working with vector databases at production scale
  • Experience implementing agentic workflows or function-calling integrations with LLMs
  • Experience working within Azure data platforms and Microsoft Fabric environments
Required Knowledge and Skills:
  • Deep understanding of LLM application architecture, including RAG, function calling, and agent orchestration patterns
  • Strong proficiency in data modeling, semantic layer design, and integration patterns across heterogeneous systems
  • Experience with vector databases, embeddings, and retrieval system design
  • Strong understanding of API design, event-driven architectures, and workflow orchestration tools
  • Excellent technical communication skills, with the ability to translate AI concepts into actionable architecture for engineering teams
Preferred Knowledge and Skills:
  • Familiarity with Azure data services (Data Factory, Synapse, Data Lake, Fabric) and Delta Lake
  • Experience with prompt engineering and AI evaluation techniques (golden datasets, LLM-as-judge, red-teaming)
  • Knowledge of document parsing, OCR, and unstructured data processing
  • Familiarity with model performance monitoring, drift detection, and observability for AI systems
Education Requirements:
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or related field
  • Equivalent combination of education and experience may be considered

About Troon:
Founded in 1990 and headquartered in Scottsdale, AZ, Troon is the world's largest professional club management company, that specializes in services in golf, hospitality, and residential communities. With more than 900 locations in 45+ states and 27+ countries, Troon is a leading employer in hospitality. Guided by values that emphasize being infectiously energetic, consciously kind, and humbly prosperous, Troon offers professionals the opportunity to grow and succeed within a globally respected organization. Learn more at www.troon.com.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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About Troon Golf

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Troon started as one facility in 1990 and has since grown to become the world's largest professional club management company. We offer careers around the world at all levels of golf operations, opportunities for professional development, growth opportunities and a comprehensive benefits package. Our goal is to create extraordinary guest and member experiences through personalized service, consistency, and uncompromising attention to detail. For more information about the Troon Experience, please visit

Industry

Fitness and sports centers, hospitality services and traveler accommodation

Company size

10,000+ Employees

Headquarters location

Scottsdale, AZ, US

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