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Vector Databases Jobs in El Cajon, CA (NOW HIRING)

Inficare Technologies

AI Architect

San Diego, CA · On-site

$67 - $88/hr

Architect RAG, agentic AI, multi-agent systems, vector databases, and knowledge management solutions * Architect AI solutions across Azure and AWS environments * Define AI governance, security ...

Petco

Sr. Engineer, AI Platform Engineering

San Diego, CA · On-site

$107K - $147K/yr

Integrate embeddings, vector databases, and cloud AI/ML services into core engineering products. MLOps, LLMOps & Infrastructure * Establish and champion MLOps and LLMOps best practices across the ...

SHEIN

Staff Database Engineer

San Diego, CA · On-site

Familiar with AI application frameworks such as LangChain and LlamaIndex, with practical experience integrating them with relational or vector databases. * Able to systematically structure and ...

SHEIN

Staff Database Engineer

San Diego, CA · On-site

Familiar with AI application frameworks such as LangChain and LlamaIndex, with practical experience integrating them with relational or vector databases. * Able to systematically structure and ...

Teradata

Senior Staff AI Engineer - 220323

San Diego, CA · On-site +1

$199K - $249K/yr

Design and implement production grade AI systems using LLMs, embeddings, vector databases, and agent based architectures. * Build scalable, secure, and reusable platform services and APIs supporting ...

Qualcomm

AI Systems Hardware Engineer

San Diego, CA · On-site

$164 - $246/hr

The focus is on identifying the system and technology bottlenecks for the state‑of‑the‑art and emerging AI workloads such as mixture‑of‑experts (MoE), multi‑tenant vector databases ...

Qualcomm

AI Systems Hardware Engineer

San Diego, CA · On-site

The focus is on identifying the system and technology bottlenecks for the state-of-the-art and emerging AI workloads e.g. the mixture-of-experts (MoE), multi-tenant vector databases, multimodal ...

PlayStation Global

AI Engineer

San Diego, CA · On-site

Contribute to RAG and agentic retrieval pipelines over enterprise content and operational data using embeddings, vector databases, hybrid search, reranking, citations, access controls, and freshness ...

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All JobsVector Databases JobsVector Databases Jobs in El Cajon, CA

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 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.

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 job categories do people searching Vector Databases jobs in El Cajon, CA look for?

The top searched job categories for Vector Databases jobs in El Cajon, CA are:

What cities near El Cajon, CA are hiring for Vector Databases jobs?

Cities near El Cajon, CA with the most Vector Databases job openings:

Vector Databases jobs near you

AI Architect

Inficare Technologies

San Diego, CA • On-site

$67 - $88/hr

Full-time

Posted 22 days ago

Job description

Job Title: AI Architect
Location: San Diego, CA (Onsite - Local Candidates Preferred)
Job Type: Full Time
Experience: 10+ years in software engineering, cloud, or enterprise architecture; 5+ years in AI/ML; 3+ years with Generative AI and LLMs
Job Overview
Key Responsibilities
  • Define and implement enterprise AI architecture frameworks, standards, and best practices
  • Design end-to-end GenAI solutions leveraging Claude, Gemini, OpenAI, and other foundation models
  • Architect RAG, agentic AI, multi-agent systems, vector databases, and knowledge management solutions
  • Architect AI solutions across Azure and AWS environments
  • Define AI governance, security, compliance, and risk management frameworks
  • Serve as a trusted advisor to executive leadership on AI strategy and emerging technologies
  • Mentor architects, engineers, and data science teams
Required Skills
  • Foundation Models: Anthropic Claude, Google Gemini, OpenAI, multi-model orchestration
  • GenAI Techniques: Prompt engineering, fine-tuning, RAG, AI agents, agentic workflows
  • Vector Databases: Pinecone, Weaviate, Milvus, Chroma, Azure AI Search
  • Frameworks: LangChain, LangGraph, LlamaIndex
  • Azure: Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, AKS, Azure Data Services, Azure Security
  • AWS: Amazon Bedrock, Amazon SageMaker, AWS Lambda, ECS/EKS, AWS Data and Analytics, AWS Security and Governance
  • Programming: Python, SQL, REST APIs, Microservices Architecture, CI/CD, DevOps
  • Ops: MLOps, LLMOps, model monitoring and evaluation
Preferred Skills
  • Experience in regulated industries: healthcare, financial services, defense, or technology
  • Enterprise AI governance and Responsible AI frameworks
  • Integration of AI solutions with ERP, CRM, and enterprise systems
  • Master's degree in Computer Science, AI, Data Science, or related field
Preferred Certifications
  • Microsoft Certified: Azure Solutions Architect Expert or Azure AI Engineer Associate
  • AWS Certified Solutions Architect Professional or Machine Learning Specialty
  • Google Professional Cloud Architect or Professional Machine Learning Engineer
Location & Work Model
Onsite - San Diego, CA. Local candidates strongly preferred.
Engagement Details
Full-Time permanent position with a leading technology organization.

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