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Vector Databases Jobs in Bridgewater, 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 ...

Tempus

Data Architect, Next Platform

Boston, MA · On-site +1

$150K - $200K/yr

Experience with Vector databases (e.g., Pinecone, Weaviate, or pgvector) or Graph databases to support RAG and agentic memory. * Cloud Architecture: Hands-on experience with GCP (BigQuery, Vertex AI ...

Accenture

AI Engineering Consultant - Utilities

Boston, MA · On-site

$70K - $205K/yr

Engineer with modern tooling - use Python, API integration, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex) to build production-ready solutions. * Apply DevOps practices ...

FocusKPI Inc.

Junior AI/ML Engineer (Remote)

Boston, MA · Remote

Knowledge of vector databases or embeddings * Familiarity with AWS, GCP, or Azure * Prior internship or project experience building AI/ML applications How to Apply Please submit the following to danz ...

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 ...

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

$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 ...

Klaviyo

Software Engineer II - Recommendations

Boston, MA · On-site

$105K - $145K/yr

Contribute to the development of the vector database that powers recommendation, semantic search, and agentic use cases. * Ensure data and service observability (metrics, logging, tracing, dashboards ...

Klaviyo

Software Engineer II - Recommendations

Boston, MA · On-site

$105K - $145K/yr

Contribute to the development of the vector database that powers recommendation, semantic search, and agentic use cases. * Ensure data and service observability (metrics, logging, tracing, dashboards ...

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 ...

Northeastern University

Senior Data Architect

Boston, MA · On-site

$130K - $189K/yr

Knowledge of AI/ML foundational components: vector databases, feature stores, RAG pipelines, metadata management. * Strong understanding of data modeling (conceptual, logical, physical), master data ...

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All JobsVector Databases JobsVector Databases Jobs in Bridgewater, MA

Vector Databases information

What are vector databases?

Vector databases are specialized databases designed to store, manage, and search high-dimensional vector data, which is commonly generated from machine learning models, such as embeddings from natural language processing or image recognition. They enable efficient similarity search operations, such as finding the most similar items to a given query vector, which is essential for applications like recommendation systems, semantic search, and AI-powered search engines. Unlike traditional databases that handle structured or unstructured data, vector databases are optimized for fast and scalable similarity searches on large datasets of vectors.

What are some common challenges faced when working with vector databases, and how can they be addressed?

Professionals working with vector databases often encounter challenges such as efficiently scaling to handle large datasets, ensuring low-latency similarity searches, and integrating the database with machine learning pipelines. To address these, teams typically implement distributed architectures, fine-tune indexing strategies, and collaborate closely with data engineers and machine learning specialists. Staying updated with the latest developments in vector database technologies and maintaining clear communication with cross-functional teams are also key to overcoming these challenges.

What are the key skills and qualifications needed to thrive as a vector database engineer, and why are they important?

Success as a Vector Database Engineer requires a strong background in computer science, database management, and experience with machine learning or AI-driven data systems. Familiarity with vector database platforms (such as Pinecone, Milvus, or Weaviate), cloud infrastructure, and proficiency in languages like Python are typically expected. Strong problem-solving skills, effective communication, and the ability to work cross-functionally help engineers stand out. These competencies are vital to efficiently design, deploy, and maintain scalable vector search solutions that power modern AI applications.

What is the difference between Vector Databases vs Data Engineers?

AspectVector DatabasesData Engineers
Required SkillsDatabase management, data modeling, query optimizationData pipeline development, ETL processes, programming
Work EnvironmentData storage systems, AI/ML projects, cloud platformsData infrastructure, cloud environments, big data tools
Industry UsageAI, machine learning, recommendation systemsData integration, analytics, data architecture

While Vector Databases focus on storing and querying high-dimensional vector data for AI applications, Data Engineers build and maintain data pipelines and infrastructure to support data analysis and machine learning workflows. Both roles are essential in data-driven industries but serve different functions within the data ecosystem.

What cities near Bridgewater, MA are hiring for Vector Databases jobs?

Cities near Bridgewater, MA with the most Vector Databases job openings:

Vector Databases jobs near you

Senior Software Engineer (AI / LLMs)

apiphani

Boston, MA • Remote

$120K - $160K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 9 days ago

Job description

Apiphani is a technology-enabled managed services company dedicated to redefining what it means to support mission-critical enterprise workloads. We're a small but rapidly growing company, which means there's lots of room for growth and learning opportunities abound! 

Apiphani is dedicated to creating a diverse and inclusive work environment for all as a fundamental component of our business. Diversity and inclusion are the bedrock of creativity and innovation. Without diversity of experience and thought, we would fail to progress as a company and as a team. Apiphani strives to foster an environment of belonging, where every employee feels respected, valued, and empowered.  We embrace the unique experiences, perspective, and cultural background, which only you can bring to the table.  

Senior Software Engineer — Agentic AI Platform 

Location: Remote | Full-time | Competitive Compensation 

Apiphani is building the future of intelligent infrastructure automation through agentic AI. We're looking for a Senior Backend Engineer to help design and build the systems that power Luumen — an AI-driven automation platform used by enterprise IT and managed service providers around the world. 

This is a high-impact, zero-to-one engineering role focused on building the backend foundations for large-scale AI orchestration. You'll work on distributed systems that combine traditional infrastructure automation with large language models (LLMs), retrieval-augmented generation (RAG), and intelligent agents. 

What You'll Do 

  • Design and implement backend services that enable intelligent agent workflows and autonomous infrastructure actions 
  • Develop APIs and orchestration layers in Python and TypeScript, integrating LLMs, vector databases, and observability pipelines 
  • Build scalable systems to support LLM-based reasoning, retrieval, and decision-making across cloud infrastructure 
  • Integrate with AWS Bedrock and other LLM platforms to support multi-model capabilities 
  • Develop data access and semantic search layers using vector databases (e.g., pgvector, Pinecone, Qdrant) 
  • Build robust monitoring, testing, and CI/CD systems to ensure reliability and reproducibility of AI workflows 
  • Collaborate closely with the product and DevOps teams to design architecture diagrams, plan deployments, and monitor system health 
  • Write clean, maintainable code with clear documentation and strong adherence to security and performance best practices 
  • Participate in code reviews, design discussions, and iterative delivery cycles to improve product velocity and quality 

What We're Looking For 

  • 6+ years of backend engineering experience in production environments 
  • Strong proficiency in Python and TypeScript for building distributed, event-driven systems 
  • Deep understanding of AWS services (Lambda, ECS, Bedrock, S3, CloudWatch, etc.) 
  • Experience designing APIs, microservices, and event pipelines that interface with LLMs or AI models 
  • Familiarity with vector databases and concepts like embeddings, similarity search, and retrieval-augmented generation 
  • Experience with infrastructure-as-code tools such as Terraform or AWS CDK 
  • Understanding of SQL and schema migration workflows (PostgreSQL or similar) 
  • Hands-on experience with Docker, GitHub Actions, and cloud-native CI/CD workflows 
  • Ability to diagram systems, communicate architecture decisions clearly, and work asynchronously in a distributed team 
  • Strong sense of ownership and ability to deliver in fast-moving, ambiguous environments 

Bonus Points 

  • Experience working with LangChain, OpenAI, or Anthropic APIs 
  • Familiarity with agentic frameworks or AI orchestration systems 
  • Background in observability or APM tooling (e.g., Datadog, Dynatrace) 
  • Prior experience building automation or infrastructure management tools 
  • Contributions to open-source LLM or MLOps projects 
  • Interest in shaping how AI is applied to real-world IT operations 

Why Join Apiphani 

You'll be joining a globally distributed, high-performing team focused on redefining how enterprises manage infrastructure. Every feature you build will directly impact how engineers interact with intelligent systems in production environments. 

This is an opportunity to help architect the foundations of a platform that blends infrastructure automation, AI, and agentic reasoning — where your technical decisions will shape the next generation of enterprise operations. 

Base Salary
$120,000—$160,000 USD
Company Benefits*
  • Medical/dental/vision - 100% paid for employees, 50% paid for dependents
  • Life and disability - 100% paid for employees
  • 401K - 3% contribution, no employee contribution necessary 
  • Education and tuition reimbursement
  • Accident, critical illness, hospital indemnity benefits offered through our providers
  • Employee Assistance Program 
  • Legal assistance
  • Paid Time Off - up to 6 weeks per year 
  • Sick Leave - up to 2 weeks per year
  • Parental Leave - up to 12 weeks 

*Benefits listed in the job description apply to employees working in the United States. For international employees, Apiphani partners with an Employer of Record, Deel, and provides all statutory benefits required under local law; certain U.S.-specific programs (such as EAP, legal assistance, etc.) may not be available outside the United States. The specific benefits package will be outlined in the local employment agreement issued through Deel.

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