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Pinecone Vector Databases Jobs (NOW HIRING)

CCS INC

AI/ML Engineer

Plano, TX · On-site

$65 - $75/hr

Deep operational expertise with vector databases, such as Pinecone, Milvus, Weaviate, or Qdrant. * AWS Solutions Architect, AWS DevOps Engineer, or equivalent industry certifications.

Robustware

AI/ML Engineer

Cupertino, CA · On-site

Expertise in Python, vector databases (Elastic, Milvus, Pinecone, etc.), embeddings, and chunking strategies * Hands-on experience with Kubernetes, Docker, and scalable API deployment * Ability to ...

Tanisha Systems, Inc.

AI/ML Engineer

Cupertino, CA · On-site

Expertise in Python, vector databases (Elastic, Milvus, Pinecone, etc.), embeddings, and chunking strategies * Hands-on experience with Kubernetes, Docker, and scalable API deployment ...

eTeam

Generative AI Developer

Denver, CO · On-site

... vector databases • Pinecone • FAISS • MLOps Systems • MLflow • model registry • CICD pipelines • Experiment tracking and automated testing • Deployment patterns • batch real-time ...

ITBMS Inc.

AI Engineer

Plano, TX · On-site

Knowledge of RAG, embeddings, and vector databases (e.g., Pinecone, FAISS, ChromaDB, Milvus). * Experience with AI frameworks such as LangChain or LlamaIndex. * Familiarity with REST APIs and Git.

New

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 ...

Euclid Innovations

ML Engineer

Charlotte, NC · On-site

... vector databases like Pinecone, Weaviate, Milvus, or FAISS • Expertise in APIs, REST, and cloud platforms (AWS, Azure, GCP) • Knowledge of distributed systems and workflow automation tools ...

Staffingine LLC

AI Engineer

Phoenix, AZ · On-site

Develop and implement AI solutions using Python and AI frameworks such as Langgraph and Langchain Work with vector databases like Pinecone to manage and query highdimensional data Build and maintain ...

CCS INC

Gen AI Engineer

Plano, TX · On-site

$40 - $50/hr

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). * Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)

CCS INC

Lead Gen AI Engineer

Plano, TX · On-site

$85 - $110/hr

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). * Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)

Precision Technologies Corp

Sr. Data/GenAI Engineer

Irving, TX · On-site

$101K - $138K/yr

... vector databases (e.g., Pinecone, Chroma, PGvector) and the concept of embeddings. o Experience working with a variety of data sources, from structured databases to semi-structured API outputs. o ...

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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.

More about Pinecone Vector Databases jobs
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Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 5% Part Time, 1% Temporary, and 7% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.

Technical Product Marketing Manager

Pinecone Systems, Inc

New York, NY • On-site

$126K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 8 days ago

Job description

About Pinecone:
Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. Pinecone's mission is to make AI knowledgeable. More than 109,000 customers across various industries have shipped AI applications faster and more confidently with Pinecone's developer-friendly technology. Pinecone is based in New York and has raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital.
About the Role/Team:
As a Technical PMM, you will help developers, software engineers, and machine learning scientists understand how Pinecone enables knowledgeable AI applications. You will accomplish this through messaging and positioning, GTM strategy, launch planning, and enablement for key product features. You will work closely with Product, Sales, Developer Relations, and Marketing teams to ensure our customers understand the value of our platform.
Responsibilities:
  • Product Launches & GTM Strategy:
    • Develop launch plans for product releases, align with product teams, and manage GTM execution.
    • Lead core launch teams with cross-functional members (documentation , communications, developer relations, product, growth marketing, etc).
    • Measure customer impact and adoption post-launch, iterating on strategies as needed.
  • Positioning & Messaging:
    • Craft compelling, technically accurate messaging for AI-powered search and retrieval solutions.
    • Build product narratives for enterprise and developer audiences that differentiate Pinecone from competitors.
    • Develop and maintain positioning for new product capabilities
  • Customer & Market Insights:
    • Partner with customers to develop case studies, gathering business impact metrics and architectural insights.
    • Engage in customer interviews and research to refine messaging and identify key value drivers.
  • Content Development & Enablement:
    • Develop internal and external enablement materials, including sales training, pitch decks, and GTM enablement sessions.
    • Collaborate with marketing to create social posts, blogs, and technical content.

Requirements:
  • 5+ years of experience in product marketing, ideally at a developer-focused or AI/ML infrastructure company.
  • Strong technical acumen with hands-on experience in AI, ML, vector search, cloud computing, or databases.
  • Proven track record in launching technical products and driving adoption in enterprise and developer communities.
  • Ability to translate complex technical concepts into clear, compelling messaging for different audiences.
  • AI-native workflow from content creation to automating away process
  • Experience working cross-functionally with Product, Engineering, Developer Relations, and Sales teams.
  • Excellent written and verbal communication skills.

Bonus points:
  • Experience in developer marketing or working directly with AI/ML practitioners.
  • Familiarity with vector databases, retrieval-augmented generation (RAG), or search technologies.
  • Knowledge of cloud infrastructure and AI model deployment.

Perks & Benefits:
  • Comprehensive health coverage including medical, dental, vision, and mental health resources
  • 401(k) Plan
  • Equity award
  • Flexible time off
  • Paid parental leave
  • Annual Company Retreat
  • WFH Equipment Stipend

All qualified applicants will receive considerations for employment without regard to race, color, religion, sex, age, disability, marital status, familial status, sexual orientation, pregnancy, gender identity, gender expression, national origin, ancestry, citizenship status, veteran status, and any other legally protected status under federal, state, or local anti-discrimination laws.

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