ZipRecruiter

Log In

1

Vector Databases Jobs in Redmond, WA (NOW HIRING)

DigitalOcean

Staff Product Manager

Seattle, WA · Hybrid

$186K - $233K/yr

Lead development of next-generation data primitives - including vector databases, knowledge bases, MCP integrations, and open table formats like Apache Iceberg - to power RAG workflows and agentic ...

Programmers.io

Azure AI/ML Engineer

Bellevue, WA · On-site

$62 - $77/hr

... experience with Vector Databases and embedding-based search e.g. Azure AI SearchPractical experience with Semantic Kernel| AI Foundry| Lang Chain| LlamaIndex| or similar frameworks| Azure ...

CipherMax LLC

Senior Java Developer

Seattle, WA · On-site

$65.25 - $83/hr

Vector Databases (Pinecone, ChromaDB, FAISS, OpenSearch) * AWS and/or Google Cloud Platform (Google Cloud Platform) * Docker, Kubernetes, CI/CD * Strong experience building enterprise-scale AI ...

Visa

Data Engineer - Senior Consultant level

Foster City, CA · On-site

$123K - $167K/yr

Explore emerging technologies across GenAI infrastructure, orchestration systems, vector databases, and cloud-native data platforms This is a hybrid position. Expectation of days in office will be ...

The Trade Desk

Sr AI Engineer

Bellevue, WA · On-site

$117K - $161K/yr

... AI Search, vector databases, and secure enterprise connectors to deliver contextual insights. • Build and deploy agents using Microsoft Copilot, Copilot Studio, Anthropic Claude, and similar ...

DigitalOcean

Staff Product Manager

Seattle, WA · On-site

$186K - $233K/yr

Lead development of next-generation data primitives - including vector databases, knowledge bases, MCP integrations, and open table formats like Apache Iceberg - to power RAG workflows and agentic ...

Visa

Data Engineer

Foster City, CA · Hybrid

$133K - $160K/yr

Explore emerging technologies across GenAI infrastructure, orchestration systems, vector databases, and cloud-native data platforms This is a hybrid position. Expectation of days in office will be ...

Amazon

Software Development Manager III, S3 Vectors

Seattle, WA · On-site

$140K - $185K/yr

... vector databases. As an SDM on S3 Vectors, you will lead a team of engineers driving fast-paced green field development of foundational services related to this new offering. S3 Vectors: As an SDM in ...

Stoke Space

Senior AI Software Engineer

Kent, WA

$154K - $231K/yr

Build and maintain RAG pipelines leveraging vector databases to enable intelligent search and retrieval * Develop comprehensive evaluation frameworks (evals) to measure, monitor, and improve AI ...

Amazon

Software Development Manager III, S3 Vectors

Seattle, WA · On-site

$140K - $185K/yr

... vector databases. As an SDM on S3 Vectors, you will lead a team of engineers driving fast-paced green field development of foundational services related to this new offering. S3 Vectors: As an SDM in ...

next page

Showing results 1-20

All JobsVector Databases JobsVector Databases Jobs in Redmond, WA

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 Redmond, WA? For Vector Databases jobs in Redmond, WA, the most frequently searched job titles are:
What job categories do people searching Vector Databases jobs in Redmond, WA look for? The top searched job categories for Vector Databases jobs in Redmond, WA are:
What cities near Redmond, WA are hiring for Vector Databases jobs? Cities near Redmond, WA with the most Vector Databases job openings:
Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Redmond, WA as of June 2026, with employment types broken down into 70% Full Time, 18% Part Time, and 12% Contract. Highlights an 73% Physical, 3% Hybrid, and 24% Remote job distribution.
Staff Product Manager

Staff Product Manager

DigitalOcean

Seattle, WA • Hybrid

$186K - $233K/yr

Other

Posted 10 days ago

Job description

We are looking for a Staff Product Manager to own the strategic vision, development, and execution of DigitalOcean's Data and AI platform. This is a high-impact, high-ownership role: you will define what we build, shape how we go to market, and drive the roadmap for our next-generation data infrastructure - a foundation that powers everything from traditional analytics to modern AI-driven applications at scale.

Data platforms have fundamentally changed. They are no longer just for reporting - they are the source of truth for AI agents, the home for vector embeddings, and the foundation for RAG-based knowledge bases. As Staff PM, you will own the core product strategy at this intersection, shaping how DigitalOcean develops, prices, and positions its data offerings as customer demand evolves toward vector databases, knowledge bases, a semantic layer for consistent metrics across agents and human interactions, and integrated AI capabilities. You will operate at the intersection of customer needs, market realities, and complex technical execution - bridging Engineering, Infrastructure, and Go-to-Market teams to ship products customers trust in production.

What You'll Do
  • Define and drive the multi-year product strategy and roadmap for DigitalOcean's Data and AI portfolio, spanning traditional analytics through modern AI-driven infrastructure.
  • Lead development of next-generation data primitives - including vector databases, knowledge bases, MCP integrations, and open table formats like Apache Iceberg - to power RAG workflows and agentic long-term memory.
  • Conduct deep market and competitive analysis to shape pricing, positioning, and go-to-market strategies in a rapidly evolving AI landscape.
  • Collaborate cross-functionally with Engineering, Infrastructure, and Capacity Planning to deliver scalable, reliable data solutions that customers rely on for production workloads.
  • Serve as the voice of the customer, gathering feedback to prioritize features that reduce operational complexity across the full data product lifecycle.
  • Define and track key performance metrics - utilization, reliability, deployment velocity - to evaluate product success and guide roadmap decisions.
What You'll Add to DigitalOcean
  • 7+ years of product management experience with a focus on cloud-native data platforms, managed databases, or large-scale analytics infrastructure.
  • Proven expertise in the full lifecycle of data or AI products - from concept and pricing through large-scale deployment.
  • Deep technical fluency in modern data patterns: vector embeddings, knowledge bases, SQL-based analytics, data lake architectures (Iceberg), and the emerging AI agent ecosystem (MCP).
  • Demonstrated ability to communicate strategic decisions to C-level executives and build alignment across diverse technical and business stakeholders.
  • Demonstrated ability to present complex technical and strategic topics to diverse audiences, including industry conferences and executive stakeholders.
  • Strong analytical background with experience in capacity planning, scaling economics, and competitive pricing models for cloud services.
  • High ownership mindset with a track record of navigating complex technical constraints to deliver measurable customer value.
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field - or equivalent practical experience building technical products.
Compensation Range: 
  •     $186,400 - $233,000

*This is a hybrid role

JR: 2026-7911

#LI-Hybrid

Apply