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Pinecone Vector Databases Jobs in Basking Ridge, NJ

Photon

Gen AI Engineer - NY

Manhattan, NY · On-site

Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., Pinecone, FAISS) * API development and integration (FastAPI, REST, microservices) * Cloud platforms: AWS / Azure / GCP ...

SysMind Tech

Gen-AI Engineers

Jersey City, NJ · On-site

$65 - $70/hr

Experience with vector databases such as Pinecone, FAISS, Chroma, Weaviate, Milvus, or Azure AI Search. * Experience with cloud platforms such as Azure, AWS, or GCP. * Good understanding of APIs ...

Photon

Gen AI Engineer - NY

Manhattan, NY · On-site

Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., Pinecone, FAISS) * API development and integration (FastAPI, REST, microservices) * Cloud platforms: AWS / Azure / GCP ...

RightTalents

Forward Deployed Engineer

Jersey City, NJ · On-site

Hands-on depth with RAG (Retrieval-Augmented Generation) architectures, vector databases (e.g., Pinecone, Milvus, Qdrant, or pgvector), and relational/non-relational systems (SQL/NoSQL). * Cloud ...

Marencor

AI Solutions Architect

New York, NY · On-site

$69 - $90.75/hr

Define architecture for RAG (retrieval augmented generation) systems using vector databases (e.g., FAISS, Pinecone) * Deploy LLM-based agents and secure GenAI pipelines (prompt injection protection ...

Velocity Search Group

Enterprise AI Architect

Manhattan, NY · On-site

$76 - $98/hr

... with vector databases and enterprise search platforms such as Pinecone, Azure AI Search, Weaviate, ChromaDB, or similar technologies. • Relevant cloud, AI, governance, or architecture ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

Familiarity with popular vector databases like Redis, Milvus, Pinecone, Weaviate, Chroma or Faiss is required. * Knowledge of machine learning techniques and algorithms, including fine tuning ...

Accenture

Knowledge Engineer - Back End

New York, NY · On-site

Minimum 3 years experience deploying and operating vector databases (e.g., Pinecone, Weaviate, Milvus, or Qdrant) in production environments. * Minimum 3 years Proficiency in Python or Java for ...

Marencor

Data/AI/ML Integration Developer

New York, NY · On-site

$55 - $60/hr

Manage vector database operations (e.g., Pinecone/Weaviate) for GenAI search augmentation * Integrate with orchestration layers for multi-agent systems using LangChain, CrewAI Required Qualifications ...

Schonfeld

AI Data Engineer

New York, NY · On-site

$125K - $150K/yr

Understanding of data requirements for ML/AI systems, including experience with vector databases (Pinecone, Weaviate, Qdrant) and embedding pipelines Preferred Experience * Experience building data ...

Capgemini

GenAI / Agentic AI Developer

New York, NY · On-site

Vector Databases * Experience working with one or more of the following: * OpenAI * Azure OpenAI ... OpenSearch * Pinecone * Chroma * FAISS * Weaviate * Milvus * Azure AI Search * pgvector

Schonfeld

AI Data Engineer

New York, NY

$125K - $150K/yr

Understanding of data requirements for ML/AI systems, including experience with vector databases (Pinecone, Weaviate, Qdrant) and embedding pipelines Preferred Experience * Experience building data ...

Capgemini

AI Solutions Developer

New York, NY · On-site

$55 - $75.75/hr

... vector databases FAISS Chroma Pinecone or similar technologies - Ability to design and implement end to end ML pipelines training validation deployment - Strong understanding of machine learning ...

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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 job categories do people searching Pinecone Vector Databases jobs in Basking Ridge, NJ look for? The top searched job categories for Pinecone Vector Databases jobs in Basking Ridge, NJ are:
What cities near Basking Ridge, NJ are hiring for Pinecone Vector Databases jobs? Cities near Basking Ridge, NJ with the most Pinecone Vector Databases job openings:
Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in Basking Ridge, NJ as of August 2026, with employment types broken down into 85% Full Time, 7% Part Time, 1% Temporary, and 7% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution.

Gen AI Engineer - NY

Photon

Manhattan, NY • On-site

Full-time, Contractor

Medical, Dental, Vision, Retirement, PTO

Re-posted 27 days ago

Job description

Core Skill Set:

  • Python (advanced, production-grade coding)
  • Generative AI (LLMs, prompt engineering, fine-tuning, RAG)
  • Agent development using frameworks such as ADK, LangGraph, LangChain

Additional Relevant Skills:

  • Experience building end-to-end AI applications (design deploy scale)
  • Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., Pinecone, FAISS)
  • API development and integration (FastAPI, REST, microservices)
  • Cloud platforms: AWS / Azure / GCP (especially AI/ML services)
  • Model evaluation, guardrails, and Responsible AI practices
  • Experimentation frameworks, prompt/version management, and observability
  • Working knowledge of data pipelines and engineering (ETL, streaming)
  • Familiarity with MLOps / LLMOps (CI/CD for models, monitoring, retraining)
  • Strong problem-solving with ability to translate business use cases into AI solutions

Compensation, Benefits and Duration

Minimum Compensation: USD 35,000
Maximum Compensation: USD 123,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post

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