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Vector Databases Jobs in New York (NOW HIRING)

MDAEdge

Senior Gen AI Developer

Brooklyn, NY · On-site

$132K - $177K/yr

LangChain, LangGraph, LlamaIndex, NLP models, RAG vector DBs, model deployment. • 7+ years database: Oracle SQL/PL-SQL, ER design, query optimization. • 7+ years microservices/web: REST APIs, MVC ...

Alpha Silicon

Senior AI Solution Architect

Raritan, NJ · On-site

Stay ahead of industry trends in Generative AI, LLMs, multimodal AI, LangChain, LangGraph, and vector databases . * Drive innovation by recommending new tools, frameworks, and approaches to maximize ...

Indicium AI

AI Engineers - USA

New York, NY · On-site

$134K - $176K/yr

Design and implement production AI systems integrating LLMs, RAG pipelines, vector databases, and agentic frameworks. * Create evaluation frameworks to measure and monitor system performance ...

Indicium AI

AI Engineers - USA

New York, NY · On-site

$134K - $176K/yr

Design and implement production AI systems integrating LLMs, RAG pipelines, vector databases, and agentic frameworks. * Create evaluation frameworks to measure and monitor system performance ...

Sweep360

Software Engineer, Product

New York, NY · On-site

$220K/yr

Built production systems using LLMs, vector databases, and retrieval pipelines. * Thrived in an early-stage startup. * U.S. Person status required. May involve export-controlled data. Bonus if you've.

Sweep360

Software Engineer, Product

New York, NY · On-site

$220K/yr

Built production systems using LLMs, vector databases, and retrieval pipelines. * Thrived in an early-stage startup. * U.S. Person status required. May involve export-controlled data. Bonus if you've.

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Vector Databases information

What is the salary of a vector database developer?

The salary of a vector database developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Skilled developers with expertise in machine learning, data structures, and database management may earn higher salaries, especially in tech hubs or with advanced certifications.

Are vector databases the future?

Vector database jobs involve managing and optimizing databases designed for high-dimensional vector data, which are essential for AI and machine learning applications. As AI continues to grow, demand for professionals skilled in vector database technologies and related tools like embedding models is expected to increase, making this a promising field for future job opportunities.

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 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 can you do with a vector database?

A vector database is used in roles involving data management and machine learning to store, search, and retrieve high-dimensional vector representations of data such as images, text, or audio. It enables efficient similarity searches, supporting applications like recommendation systems, natural language processing, and computer vision. Working with a vector database often requires knowledge of data structures, indexing techniques, and programming skills in languages like Python or C++.

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 are the top 5 vector databases?

Top vector databases used in data management and AI applications include Pinecone, Weaviate, FAISS, Milvus, and Annoy. These databases are optimized for storing and searching high-dimensional vector data, often requiring skills in machine learning and database management. They are widely adopted for tasks like similarity search and recommendation systems.
What are popular job titles related to Vector Databases jobs in New York? For Vector Databases jobs in New York, the most frequently searched job titles are:
What job categories do people searching Vector Databases jobs in New York look for? The top searched job categories for Vector Databases jobs in New York are:
What cities in New York are hiring for Vector Databases jobs? Cities in New York with the most Vector Databases job openings:
Vector Databases jobs near you
Infographic showing various Vector Databases job openings in New York as of July 2026, with employment types broken down into 66% Full Time, and 34% Contract. Highlights an 89% In-person, and 11% Remote job distribution.

Senior Gen AI Developer

MDAEdge

Brooklyn, NY • On-site

$132K - $177K/yr

Full-time

Posted 24 days ago

Job description

Job Summary:
MDAEdge is a company seeking a Senior Gen AI Developer. The role involves designing and developing web applications and APIs, fine-tuning language models, and optimizing database performance while ensuring security and compliance.
Responsibilities:
• Design and develop web apps, APIs, microservices using C#, .NET Core, REST, modern UI frameworks.
• Fine-tune and deploy LLMs (Claude, ChatGPT) using AWS Bedrock and Python frameworks.
• Optimize, design, deploy RAG vector databases.
• Optimize database performance, manage stored procedures, ensure data quality in Oracle and cloud platforms.
• Deploy/monitor apps and models via CI/CD (Docker, Kubernetes, GitHub Actions, Azure DevOps, Jenkins) and MLOps/LLMOps.
• Ensure security, compliance, logging, observability, performance tuning.
• Participate in requirements review, sprint planning, code reviews, release management, documentation.
• Support production releases, troubleshoot, resolve issues timely.
Qualifications:
Required:
• 10+ years programming: .NET Core, C#, Python.
• 5+ years AI/ML/NLP: LangChain, LangGraph, LlamaIndex, NLP models, RAG vector DBs, model deployment.
• 7+ years database: Oracle SQL/PL-SQL, ER design, query optimization.
• 7+ years microservices/web: REST APIs, MVC, Web API, JSON, OAuth, SSO, microservices architecture.
• 7+ years cloud/DevOps: AWS/Azure/GCP, Docker, CI/CD, API gateways, Bedrock, SageMaker.
• 10+ years debugging, performance tuning, security practices.
• 10+ years delivering mid-to-large enterprise apps/integrations.
• Database optimization and data quality management.
• CI/CD pipeline deployment for AI models.
• Collaborative in Agile processes: sprint planning, code reviews, issue resolution.
• 10+ years total relevant experience.
• Bachelor's degree in Computer Science, Information Technology, or related field.
• English native or bilingual proficiency.
Preferred:
• NY local resident preferred
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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