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Pinecone Vector Databases Jobs in Massachusetts (NOW HIRING)

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 ...

Epsilon

Senior Software Engineer

Wakefield, MA · On-site

$129K - $170K/yr

Familiarity with vector databases (Pinecone, pgvector, OpenSearch) for semantic search or RAG pipelines * Experience evaluating and fine-tuning LLM outputs for accuracy, safety, and cost efficiency ...

Monotype

AI Architect

Woburn, MA · On-site

$69 - $90.75/hr

Experience with vector databases or search platforms such as Pinecone,Weaviate, Milvus,pgvector, Elasticsearch, OpenSearch, or Azure AI Search * Experience with automation and integration platforms ...

Monotype Imaging, Inc.

AI Architect

Woburn, MA · On-site

Experience with vector databases or search platforms such as Pinecone, Weaviate, Milvus, pgvector, Elasticsearch, OpenSearch, or Azure AI Search * Experience with automation and integration platforms ...

Brown Brothers Harriman & Co.

Senior AI Engineer

Boston, MA · On-site

$175K - $215K/yr

Vector databases - Pinecone, Weaviate, pgvector, or comparable * Active user of AI coding assistants in daily workflow Nice to Have * Financial services or data domain background - understanding of ...

Brown Brothers Harriman & Co.

Senior AI Engineer

Boston, MA · On-site

$175K - $215K/yr

Vector databases - Pinecone, Weaviate, pgvector, or comparable * Active user of AI coding assistants in daily workflow Nice to Have * Financial services or data domain background - understanding of ...

Photon

Principal Data Scientist

Boston, MA · On-site

... architectures, vector search ecosystems (Pinecone, Qdrant, OpenSearch, pgvector), and hybrid ... Hands-on expertise with GraphRAG, Knowledge Graphs, and graph databases (Neo4j). Strong background ...

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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

Software Architect

Motion Recruitment

Framingham, MA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Company Overview
A modern, tech-forward insurance agency operating on an AI-native brokerage platform. The mission is to leverage the latest technology and innovation to create better outcomes for agents, customers, and local communities. The platform simplifies the "agent desktop," allowing agents to focus on customer interactions while automating complex workflows through natural language interfaces and evolving based on behavioral data. Role Overview Seeking an experienced Software Architect to lead the design and development of the next generation of an AI-powered insurance platform. This role will drive architectural decisions across the stack, including modern web applications, scalable microservices, integrations, and APIs, ensuring systems are robust, scalable, and maintainable.
This position partners cross-functionally with Product, Engineering, Business, Data, Finance, and Operations teams to define technical strategy and support a high-growth environment. What You'll Do • Design AI-Powered Systems: Architect and guide the implementation of agentic AI workflows to automate and enhance solutions for agents and customers
• Microservices Architecture: Define and evolve Java and Spring-based microservices architecture to enable scalable, loosely coupled, and resilient systems
• Integration Engineering: Architect integrations with external systems and define API standards for internal and external consumption
• Frontend Architecture: Define scalable frontend architecture with modular components while minimizing technical debt
• Application Development: Guide the design and development of high-performance enterprise web applications using Next.js, React, Tailwind CSS, and related technologies
• Monitoring & Observability: Establish monitoring and observability strategies to ensure system health, reliability, and performance
• Quality & Engineering Standards: Define testing strategies including component, integration, and end-to-end automation standards
• Data Engineering: Provide architectural guidance on data migration, ETL processes, and overall data flow design
• User Experience: Ensure responsive interfaces that function seamlessly across devices and browsers
• Cross-Team Collaboration: Partner with product managers, designers, and engineers to translate business requirements into scalable technical solutions
• Technical Documentation: Define and maintain architecture documentation, design standards, and key technical decisions Requirements – What You Bring • Bachelor's degree in Computer Science or a related field
• 8+ years of experience building enterprise applications
• Proven experience in a software architect, staff, or principal engineering role
• Strong understanding of microservices architecture and distributed systems design
• Expertise in Enterprise Java and Spring stack (Spring Boot, Spring Cloud, Spring Data, Spring AI)
• Proficiency in modern frontend frameworks such as React, Vue, or Svelte, with strong knowledge of component-based architecture and state management
• Strong command of HTML, CSS, and frameworks such as Tailwind CSS
• Experience designing systems that handle streaming and real-time AI outputs such as WebSockets and server-sent events
• Experience with Next.js and server-side rendering concepts
• Knowledge of state management solutions such as Redux, Zustand, or Context API
• Strong understanding of relational databases and SQL
• Experience designing and governing RESTful APIs
• Experience architecting and integrating LLM-based workflows and AI capabilities
• Working knowledge of AWS services including SQS, SNS, S3, RDS, and Lambda
• Experience with CI/CD pipelines and DevOps practices Preferred Qualifications • Experience with 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 and Kubernetes
• Familiarity with message queues and event-driven architecture
• Experience with testing frameworks such as JUnit, Mockito, or TestContainers
• Experience optimizing performance and scalability in high-traffic systems
• Understanding of caching strategies using Redis or Memcached
• Experience with observability tools such as Prometheus, Grafana, New Relic, or Datadog What Makes You Stand Out • Experience in Insurtech or Fintech environments
• Experience implementing AI or ML solutions in production
• Experience driving architectural decisions and technical direction across teams

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