ZipRecruiter

Log In

1

Pinecone Vector Databases Jobs in Oregon (NOW HIRING)

LTS

AI Platform and Harness Engineer

OR · On-site +1

Experience with vector databases including Pinecone, Qdrant, Weaviate, Azure AI Search, or pgvector. * Experience with OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude, Google Vertex AI, or ...

Tebra

Senior AI Automation Engineer

OR · On-site +1

$103K - $136K/yr

Experience using vector databases such as Pinecone, Snowflake Cortex Search, and pgvector for Retrieval-Augmented Generation (RAG). * Experience with AI/ML concepts and implementing agentic ...

Gnostech LLC

Software Engineer (US-Remote)

OR · On-site +1

Experience with vector databases or embeddings systems (Pinecone, Weaviate, Elasticsearch, etc.). * Experience implementing MLOps pipelines for model deployment and monitoring. * Experience with ...

Particle41

AI Engineer

OR · On-site +1

Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. * Experience building or fine-tuning Large Language Models (LLMs). * Experience deploying models into production ...

Grafana Labs

Staff AI Engineer | US | Remote

OR · On-site +1

Experience with vector databases or retrieval pipelines (Pinecone, Weaviate, ChromaDB, Qdrant, pgvector) * Familiarity with marketing or sales platforms (Salesforce, Customer.io, HubSpot, Marketo ...

All JobsPinecone Vector Databases JobsPinecone Vector Databases Jobs in Oregon

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 Oregon?

For Pinecone Vector Databases jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Pinecone Vector Databases jobs in Oregon look for?

The top searched job categories for Pinecone Vector Databases jobs in Oregon are:

Pinecone Vector Databases jobs near you

AI Architect/ AI Consultant

Syntricate Technologies

Portland, OR • On-site

Full-time

Re-posted 9 days ago

Job description

Job Summary:
Syntricate Technologies is seeking an AI Architect/ AI Consultant with extensive experience in AI and machine learning. The role involves building AI solutions, developing RESTful APIs, and working with cloud data and AI stacks.
Responsibilities:
• Strong proficiency in Python and its libraries for AI, machine learning, and data manipulation.
• Extensive experience in building RESTful APIs using design principles, including versioning, error handling, and pagination.
• Experience in Generative AI stack – Large Language Models / Foundation Models, vector databases e.g., Pinecone, Chroma, orchestration stack.
• Hands on experience in building AI orchestration with frameworks like LangChain.
• Strong understanding of cloud data & AI stack on Azure / AWS.
• Understanding of data processing frameworks e.g., Data Bricks, Airflow etc.
• Proficiency in JavaScript, including experience with React JS and NodeJS.
• Solid understanding of AI concepts, algorithms, and methodologies.
• Solid knowledge of databases, such as MongoDB, MySQL, or PostgreSQL, and proficiency in writing efficient queries.
• Experience with authentication and authorization protocols (e.g., OAuth, JWT) and securing APIs.
• Strong understanding of microservices architecture and familiarity with related technologies (e.g., Docker, Kubernetes).
• Familiarity with API management platforms and tools (e.g., Azure API Management, AWS API Gateway).
• Excellent problem-solving and analytical skills, with the ability to troubleshoot and debug complex API issues.
• Knowledge of serverless architecture and experience with serverless computing platforms/services (e.g., Azure Functions, AWS Lambda).
• Passion for technology and a strong ambition to excel in the field of AI.
Qualifications:
Required:
• 12+ Years experience
• Strong proficiency in Python and its libraries for AI, machine learning, and data manipulation.
• Extensive experience in building RESTful APIs using design principles, including versioning, error handling, and pagination.
• Experience in Generative AI stack – Large Language Models / Foundation Models, vector databases e.g., Pinecone, Chroma, orchestration stack.
• Hands on experience in building AI orchestration with frameworks like LangChain.
• Strong understanding of cloud data & AI stack on Azure / AWS.
• Understanding of data processing frameworks e.g., Data Bricks, Airflow etc.
• Proficiency in JavaScript, including experience with React JS and NodeJS.
• Solid understanding of AI concepts, algorithms, and methodologies.
• Solid knowledge of databases, such as MongoDB, MySQL, or PostgreSQL, and proficiency in writing efficient queries.
• Experience with authentication and authorization protocols (e.g., OAuth, JWT) and securing APIs.
• Strong understanding of microservices architecture and familiarity with related technologies (e.g., Docker, Kubernetes).
• Familiarity with API management platforms and tools (e.g., Azure API Management, AWS API Gateway).
• Excellent problem-solving and analytical skills, with the ability to troubleshoot and debug complex API issues.
• Knowledge of serverless architecture and experience with serverless computing platforms/services (e.g., Azure Functions, AWS Lambda).
• Passion for technology and a strong ambition to excel in the field of AI.
Company:
Syntricate Technologies offers quality assurance, validation, regulatory, business analysis, and project management services. Founded in 2004, the company is headquartered in Boston, USA, with a team of 51-200 employees. The company is currently Growth Stage.

Apply