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Vector Databases Jobs in New York (NOW HIRING)

Photon

AI Engineer - NY

Manhattan, NY

Integrate agents with vector databases, RAG pipelines, and knowledge graphs. Production AI Systems * Implement observability, evaluation, and guardrails for agent behavior. * Optimize AI pipelines ...

Photon

Sr Gen AI Engineer - NY/NJ

Manhattan, NY

PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, and LLM monitoring. Tools: Prompt ...

Accord Technologies Inc.

Senior AI Engineer

Piscataway, NJ · On-site

$106K - $146K/yr

Design and implement solutions involving Large Language Models (LLMs), embeddings, vector databases, Retrieval-Augmented Generation (RAG), and prompt engineering. * Work with cloud AI services such ...

Hirekeyz Inc

Agentic AI Developer

Berkeley Heights, NJ · On-site

... vector databases and graph databases. You'll own end-to-end delivery: ingestion → retrieval → agent orchestration → evaluation → deployment. What you'll do * Design and implement RAG ...

Inizio Partners Corp

Agentic AI Specialist

New York, NY · On-site

Design and maintain RAG pipelines, embeddings, vector databases, and memory/state management for contextual grounding. * Build secure and scalable backend APIs and services to support agent execution ...

Pyramid Consulting, Inc.

AI Architect

Manhattan, NY

$152K - $155K/yr

Data Modeling, Generative & Agentic AI, Machine Learning, Python, Embeddings & Vector Databases * Proven experience in architecting enterprise-grade AI/ML platforms and solutions * Technical ...

IT First Source

Agentic AI Lead

Berkeley Heights, NJ · Hybrid

$146K - $179K/yr

... vector databases and graph databases. You'll own end-to-end delivery: ingestion → retrieval → agent orchestration → evaluation → deployment. What you'll do · Design and implement RAG ...

Okaya Corp.

GEN AI Consultant

Jersey City, NJ · On-site

... vector databases and prompt engineering Build Agentic AI systems capable of autonomous task execution decisionmaking and multistep reasoning using frameworks like LangChain Agents AutoGPT or ...

IT First Source

Agentic AI Lead

Berkeley Heights, NJ · Hybrid

$146K - $179K/yr

... vector databases and graph databases. You'll own end-to-end delivery: ingestion → retrieval → agent orchestration → evaluation → deployment. What you'll do · Design and implement RAG ...

Inizio Partners Corp

AI Architect

New York, NY · On-site

Design robust RAG (Retrieval-Augmented Generation) strategies using Azure AI Search and vector databases to enable deep-context searching across customer risk profiles. * Tooling & Connectivity:

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All JobsVector Databases JobsVector Databases Jobs in New York

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 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 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 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 June 2026, with employment types broken down into 86% Full Time, 8% Part Time, 3% Temporary, and 3% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.
AI Engineer - NY

AI Engineer - NY

Photon

Manhattan, NY

Other

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago

Job description

Key Responsibilities Agentic AI Development
  • Design and implement autonomous AI agents capable of reasoning, planning, and executing multi-step workflows.
  • Develop multi-agent systems that collaborate to solve complex tasks.
  • Build tool-using agents that interact with APIs, databases, and enterprise services.
LLM Orchestration
  • Develop AI pipelines using LangChain, LangGraph, and related frameworks.
  • Implement prompt engineering, memory systems, and reasoning chains.
  • Integrate LLMs such as OpenAI, Anthropic, Gemini, or open-source models.
Agent Frameworks & ADK
  • Build production-ready agents using Agent Development Kits (ADK).
  • Implement tool registries, agent planning systems, and execution loops.
  • Develop modular agent architectures that support extensibility and reliability.
Frontend AI Interaction (React Loop)
  • Build interactive AI-driven user experiences using React Loop or similar frameworks.
  • Design real-time interfaces for agent interaction, monitoring, and feedback loops.
  • Implement streaming responses and agent status visualizations.
Backend & Infrastructure
  • Develop scalable AI services using Python (FastAPI, Flask, or similar).
  • Integrate agents with vector databases, RAG pipelines, and knowledge graphs.
Production AI Systems
  • Implement observability, evaluation, and guardrails for agent behavior.
  • Optimize AI pipelines for latency, cost, and reliability.
  • Ensure security, governance, and compliance for AI systems.
Required Qualifications
  • 7+ years of software engineering experience.
  • Strong expertise in Python for AI/ML development.
  • Hands-on experience with LangChain / LangGraph.
  • Experience building agentic AI systems or autonomous agents.
  • Experience with React-based AI interfaces (React Loop or similar).
  • Familiarity with vector databases (Pinecone, Weaviate, FAISS, etc.).
  • Experience with ADK (Agent Development Kit) frameworks.
  • Experience building multi-agent systems.
  • Knowledge of RAG architectures and knowledge retrieval systems.

  • Compensation, Benefits and Duration

    Minimum Compensation: USD 40,000
    Maximum Compensation: USD 141,000
    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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