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Pinecone Vector Databases Jobs (NOW HIRING)

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 ...

TMS

AI/ ML Engineer

New York, NY · Remote

$60 - $62/hr

Knowledge of vector databases (Pinecone, FAISS, Weaviate, ChromaDB) * Experience with REST APIs and microservices * Familiarity with cloud platforms (AWS, Azure, or GCP) Good to Have * Experience ...

INFOSYS NOVA HOLDINGS LLC

Gen. AI Engineer

Fort Worth, TX · On-site

$100K - $160K/yr

Experience building Retrieval-Augmented Generation (RAG) solutions and working with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search. * Experience with Agentic AI ...

Cliff Services Inc

AI/LLM Eng

Jersey City, NJ · On-site

... Vector databases (pgvector, Pinecone, Chroma, etc.) Python backend development (FastAPI/Flask) API integrations and workflow orchestration Deep Learning & Machine Learning (model training, fine ...

ITBMS Inc.

AI/ML Engineer with Agentic AI

Plano, TX · On-site

Retrieval-Augmented Generation (RAG) : • Work with embedding models, vector databases, context windows, and chunking strategies • Work experience in Vector database (FAISS, Milvus, Pinecone or ...

Dminds Solutions Inc.

Data Analyst

Phoenixville, PA · On-site

Familiarity with vector databases (e.g., Pinecone, Milvus) and frameworks like Hugging Face or LangChain. * Expertise in ETL/ELT pipeline design and data warehousing * Bachelors in Computer Science ...

AEG

Product Developer- CH- AXS

Charlotte, NC · On-site

... vector databases (e.g., Pinecone, Weaviate, Upstash Vector) • Experience with edge computing or serverless platforms • Background in developer platforms or API-first products • Knowledge of ML ...

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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.

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Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in the United States as of July 2026, with employment types broken down into 9% Internship, 52% Full Time, and 39% Contract. Highlights an 87% In-person, and 13% Remote job distribution.
Gen AI Engineer

Gen AI Engineer

CCS INC

Plano, TX • On-site

$40 - $50/hr

Full-time

Medical, Dental, Vision, PTO

Posted 22 days ago

Job description

Benefits:
  • Bonus based on performance
  • Competitive salary
  • Dental insurance
  • Health insurance
  • Paid time off
  • Vision insurance

Qualifications:
  • 10+ years of software engineering and development experience
  • Strong experience in building and deploying GenAI applications in production.
  • Strong programming with Python and familiar with GenAI libraries (Transformers, LangChain, Hugging Face, etc.).
  • Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate).
  • Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
  • Familiarity with CI/CD for ML workflows and versioning tools like MLflow or DVC.
  • Hands-on experience designing and building cloud-native solutions (preferably on AWS)
  • GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, LangChain, Bedrock) will be a PLUS
  • Familiar  with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex) is a PLUS
  • AWS AI certification
  • Financial Services experience
Responsibilities:
  • Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval-augmented generation (RAG).
  • Fine-tune foundation models using domain-specific data.
  • Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback (RLHF).
  • Integrate GenAI capabilities into enterprise platforms using APIs, SDKs, and orchestration tools.
  • Implement responsible AI practices including bias detection, hallucination mitigation, and explainability.
  • Drive experimentation with new models, agents, and frameworks (e.g., LangChain, LlamaIndex, OpenAI, Anthropic, etc.).