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Pinecone Vector Databases Jobs in California (NOW HIRING)

VDart, Inc.

Python Engineer

San Jose, CA · On-site

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/Google Cloud ...

TechnoSphere, Inc.

Python Engineer

San Jose, CA

$10/hr

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/GCP, and ...

K-Tek Resourcing LLC

Python Developer

San Jose, CA · On-site

$59 - $81.25/hr

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/Google Cloud ...

Cynet Systems

Python Backend Developer

San Jose, CA · On-site

$60 - $65/hr

Experience with vector databases such as Pinecone or Weaviate. * Familiarity with AI workflow frameworks such as LangChain or Llama Index. * Experience with Docker and cloud platforms such as AWS or ...

Diverse Lynx

Python Backend Engineer

San Jose, CA · On-site

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). * Infrastructure: Proficiency with Docker, AWS/GCP, and ...

Innowhyte Inc

Build and implement RAG pipelines with vector databases (e.g., Pinecone, FAISS). Develop Generative AI solutions, including chatbots, summarization, and content creation tools. Preprocess, clean, and ...

Diverse Lynx

Python Engineer

San Jose, CA · On-site

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/GCP, and ...

Diverse Lynx

Python Developer

Santa Clara, CA · On-site

$58.50 - $80.75/hr

Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate). Infrastructure: Proficiency with Docker, AWS/GCP, and ...

New

Apple

AI Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

... with vector databases (Pinecone, Weaviate, Chroma), embedding generation pipelines, document stores (MongoDB or similar) and their integration patterns Understanding of RAG, MCP architectures ...

Symhas

Gen AI Lead - RAG Specialist

Pleasanton, CA · On-site

Expertise with vector databases (Pinecone, Weaviate, pgvector, Qdrant, etc.) * Strong experience with embedding models, chunking strategies, and retrieval optimization * Proficiency in Python, LLM ...

Aptino

AI Engineer / Developer

Santa Clara, CA · On-site

$133K - $160K/yr

Experience with vector databases (Pinecone, FAISS, Weaviate, Milvus) * Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) * Experience with MLOps tools and practices

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Pinecone Vector Databases information

What is a Pinecone Vector Database?

A Pinecone Vector Database is a cloud-based service designed to efficiently store, index, and search high-dimensional vector data, such as embeddings generated by machine learning models. It enables fast similarity search, making it ideal for use cases like semantic search, recommendation systems, and AI-powered applications. Pinecone handles the complexity of scaling and managing vector data, so developers can focus on building intelligent applications without worrying about infrastructure.

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

To thrive as a Pinecone Vector Database Engineer, you need a strong background in computer science, data engineering, and experience with large-scale distributed systems, often supported by a relevant degree or equivalent experience. Proficiency in Python, REST APIs, cloud platforms (AWS, GCP), and vector search technologies, along with familiarity with Pinecone’s SDK and database management, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with cross-functional teams and deliver scalable solutions. These skills ensure robust database performance, efficient data retrieval, and successful integration of vector search capabilities into real-world applications.

What are some common challenges faced by engineers working with Pinecone Vector Databases, and how can they be addressed?

Engineers working with Pinecone Vector Databases often encounter challenges such as optimizing vector search performance at scale, ensuring data consistency across distributed systems, and integrating the database with various machine learning pipelines. Addressing these challenges typically involves tuning indexing parameters, monitoring resource utilization, and collaborating closely with data scientists to understand retrieval requirements. Regularly reviewing documentation and participating in community forums can also help engineers stay current with best practices and new features.

What is the difference between Pinecone Vector Databases vs Data Engineers?

AspectPinecone Vector DatabasesData Engineers
Primary RoleManaging and deploying vector database solutions for AI/ML applicationsDesigning, building, and maintaining data pipelines and infrastructure
Skills & CertificationsKnowledge of vector databases, cloud platforms, programming (Python, SQL)Data modeling, ETL processes, cloud services, programming (Python, Java)
Work EnvironmentTech companies, AI startups, cloud providersData-driven organizations, tech firms, finance, healthcare

While Pinecone Vector Databases specialists focus on deploying and managing vector database solutions for AI applications, Data Engineers build and maintain the data infrastructure that supports these systems. Both roles require programming skills and familiarity with cloud platforms, but their core responsibilities differ: one centers on database management, the other on data pipeline development.

What are popular job titles related to Pinecone Vector Databases jobs in California? For Pinecone Vector Databases jobs in California, the most frequently searched job titles are:
What job categories do people searching Pinecone Vector Databases jobs in California look for? The top searched job categories for Pinecone Vector Databases jobs in California are:
What cities in California are hiring for Pinecone Vector Databases jobs? Cities in California with the most Pinecone Vector Databases job openings:
Pinecone Vector Databases jobs near you
Python Backend Engineer

Python Backend Engineer

TechnoSphere, Inc.

San Jose, CA

$10/hr

Contractor

Posted 23 days ago

Job description

Mandatory Skills
Language: Expert-level proficiency in Python (3.10+ preferred).
Frameworks: Deep experience with FastAPI, Django
AI Tooling: Familiarity with LangChain, LlamaIndex, or similar frameworks for agentic workflows.
Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate).
Infrastructure: Proficiency with Docker, AWS/GCP, and asynchronous task queues
Role Overview:
We are looking for a Python Backend Engineer to build the backbone of our platform. You will be responsible for creating high-performance APIs, integrating advanced AI agent logic, and ensuring our infrastructure remains rock-solid as we scale. If you enjoy solving complex architectural puzzles and want to work at the intersection of traditional backend engineering and AI
Core Responsibilities
Scalable API Development: Design, build, and maintain robust, high-throughput APIs (FastAPI, Django, or Flask) capable of handling millions of requests.
Agent Logic Integration: Architect the backend systems that power our AI agents, managing long-running tasks, state persistence, and seamless communication between LLMs and our core services.
Authentication & Security: Implement and manage secure identity protocols (OAuth2, JWT, OpenID Connect) to protect user data and internal endpoints.
Routing & Orchestration: Design efficient request routing and service communication patterns using tools like API Gateways, or Service Meshes.
Required Technical Skills
Language: Expert-level proficiency in Python (3.10+ preferred).
Frameworks: Deep experience with FastAPI, Django
AI Tooling: Familiarity with LangChain, Llama Index, or similar frameworks for agentic workflows.
Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate).
Infrastructure: Proficiency with Docker, AWS/GCP, and asynchronous task queues