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Pinecone Vector Databases Jobs in Boston, MA (NOW HIRING)

SevenAI

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

Tool fluency - comfortable with RAG, vector databases (e.g., Pinecone/Weaviate), workflow frameworks (LangChain, Dust), and related tooling. * Architectural thinker - you can diagram end-to-end ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$30 - $35/hr

LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) Experience in RAG (Retrieval-Augmented Generation) implementations. Knowledge of MLOps tools and ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$35 - $45/hr

Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) * Experience in RAG (Retrieval-Augmented Generation) implementations. * Knowledge of MLOps tools and CI/CD pipelines. * Experience with ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$124K - $149K/yr

LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) Experience in RAG (Retrieval-Augmented Generation) implementations. Knowledge of MLOps tools and ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$32 - $35/hr

LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) Experience in RAG (Retrieval-Augmented Generation) implementations. Knowledge of MLOps tools and ...

Chewy

Software Engineer III

Boston, MA · On-site +1

$141K - $225K/yr

Understanding of LLM architectures, embeddings, and vector databases (e.g., Qdrant, Pinecone, Milvus, FAISS). * Demonstrated ability to drive cross-team technical initiatives and influence ...

Career Site

Lead AI Engineer

Quincy, MA · On-site +1

$180K - $280K/yr

Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines using advanced vector databases (e.g., FAISS, Pinecone, Milvus). * Build and enhance agentic AI systems utilizing ...

Granite Telecommunications

Lead AI Engineer

Quincy, MA · On-site

$180K - $280K/yr

Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines using advanced vector databases (e.g., FAISS, Pinecone, Milvus). * Build and enhance agentic AI systems utilizing ...

The Mutual Group

Lead AI Engineer - AWS Platform

Boston, MA · On-site +1

$130K - $190K/yr

Experience with vector databases (Pinecone, Weaviate, etc.) * Experience in regulated industries (insurance, finance, healthcare) * Exposure to microservices and containerized environments (Docker ...

The Hollister Group

AI Developer

Boston, MA · On-site

$70 - $110/hr

Build retrieval-augmented generation (RAG) systems using Azure AI Search, Amazon Kendra, or vector databases like Pinecone, Weaviate, or FAISS. * Deploy and manage models on Azure Machine Learning ...

Eisneramper Llp

AI Solution Architect

Boston, MA · On-site +1

$68.50 - $90.25/hr

Vector Databases: Azure Cosmos DB, Pinecone, or Weaviate * DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes About EisnerAmper: EisnerAmper is one of the largest accounting, tax, and ...

Lindsay & Brownell

AI Solution Architect

Boston, MA · On-site +1

$68.50 - $90.25/hr

Vector Databases: Azure Cosmos DB, Pinecone, or Weaviate * DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes About EisnerAmper: EisnerAmper is one of the largest accounting, tax, and ...

EisnerAmper

AI Solution Architect

Boston, MA · On-site

$68.50 - $90.25/hr

Vector Databases: Azure Cosmos DB, Pinecone, or Weaviate * DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes About EisnerAmper: EisnerAmper is one of the largest accounting, tax, and ...

Motion Recruitment

Software Architect

Framingham, MA · On-site

... vector databases such as PGVector, Pinecone, Weaviate, or Milvus • Experience with cloud platforms including AWS, Azure, or GCP • Knowledge of containerization and orchestration such as Docker ...

Klaviyo

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

... systems, vector databases (Pinecone, Weaviate, pgvector), and embedding models. • Proficiency with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and ...

Klaviyo

Senior AI Application Engineer

Boston, MA · On-site

... systems, vector databases (Pinecone, Weaviate, pgvector), and embedding models. • Proficiency with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and ...

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All JobsPinecone Vector Databases JobsPinecone Vector Databases Jobs in Boston, MA

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 Boston, MA? For Pinecone Vector Databases jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Pinecone Vector Databases jobs in Boston, MA look for? The top searched job categories for Pinecone Vector Databases jobs in Boston, MA are:
What cities near Boston, MA are hiring for Pinecone Vector Databases jobs? Cities near Boston, MA with the most Pinecone Vector Databases job openings:
Pinecone Vector Databases jobs near you

Senior Fullstack Engineer, Boston

Venus Consultancy

Cambridge, MA • On-site

Full-time

Posted 15 days ago

Job description

About Us

We are a fast-growing GenAI startup building intelligent, production-grade applications powered by large language models and modern cloud infrastructure. Our mission is to transform how businesses interact with data and automation through AI-first products.

Role Overview

We are seeking a talented Full Stack Engineer to help design, build, and scale our GenAI platform. You will work across frontend, backend, and AI-integrated services, collaborating closely with product, ML, and design teams to deliver impactful user experiences.

Responsibilities

  • Design and develop scalable frontend applications using React / Next.js (or similar frameworks)

  • Build backend APIs and services using Python, Node.js, or Go

  • Integrate GenAI/LLM workflows (OpenAI, Anthropic, HuggingFace, etc.) into production systems

  • Develop secure, high-performance REST/GraphQL APIs

  • Work with vector databases and traditional data stores (Postgres, Redis, Pinecone, Weaviate, etc.)

  • Implement authentication, authorization, and observability best practices

  • Deploy and maintain cloud infrastructure on AWS/GCP/Azure

  • Collaborate with ML engineers on model serving and inference pipelines

  • Participate in architecture discussions and contribute to technical direction

  • Own features end-to-end—from concept to production

Required Qualifications

  • Strong experience in Full Stack development (frontend + backend)

  • Proficiency in JavaScript/TypeScript and one backend language (Python preferred)

  • Experience with modern frontend frameworks (React/Next.js/Vue)

  • Hands-on experience building APIs and microservices

  • Familiarity with cloud platforms and CI/CD pipelines

  • Solid understanding of databases and system design

  • Passion for startups, ownership, and rapid iteration

Nice to Have

  • Experience working with LLMs or GenAI frameworks (LangChain, LlamaIndex, etc.)

  • Knowledge of vector databases and RAG pipelines

  • DevOps experience (Docker, Kubernetes, Terraform)

  • Prior startup experience

What We Offer

  • Opportunity to build cutting-edge GenAI products from the ground up

  • High ownership and real impact on product direction

  • Collaborative, fast-paced startup culture

  • Competitive salary + equity

  • Flexible work environment

  • Learning budget and career growth opportunities