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Vector Databases Jobs in Seattle, WA (NOW HIRING)

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 ...

Google

Engineering Manager, Spanner Search

Kirkland, WA · On-site

Preferred : • Experience designing, building, or operating large-scale search systems, information retrieval pipelines, or vector databases (e.g., Elasticsearch, Lucene, Pinecone, Milvus). • ...

New

Visa

Data Engineer - Senior Consultant level

Bellevue, WA · Hybrid

$119K - $162K/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 ...

Visa

Data Engineer - Senior Consultant level

Bellevue, WA · On-site

$119K - $162K/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 ...

Blue Rose Technologies LLC

AI Engineer

Seattle, WA

Experience with RAG frameworks and vector databases (Pinecone, FAISS, OpenSearch) * Knowledge of AWS services (Lambda, S3, API Gateway, IAM) Preferred: * Retail domain experience * LangChain or ...

New

Visa

Data Engineer

Bellevue, WA · Hybrid

$129K - $155K/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 ...

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All JobsVector Databases JobsVector Databases Jobs in Seattle, WA

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 Seattle, WA? For Vector Databases jobs in Seattle, WA, the most frequently searched job titles are:
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What cities near Seattle, WA are hiring for Vector Databases jobs? Cities near Seattle, WA with the most Vector Databases job openings:
Vector Databases jobs near you

Adversarial Machine Learning Engineer

C-Serv

Seattle, WA • On-site

Full-time

Medical, Life

Posted 14 days ago

Job description

The Opportunity

We are building a dedicated AI Red Team to rigorously test and harden enterprise-scale AI products.

We are looking for an adversarial machine learning specialist who thinks like an attacker.

This role focuses on identifying vulnerabilities in LLM-driven systems, breaking model guardrails, exploiting data pathways, and stress-testing AI deployments before they reach enterprise customers.

This is a hands-on technical role at the core of AI security.

What You’ll Do
  • Conduct adversarial testing across LLM and AI-based systems
  • Execute real-world attack simulations, including:
  • Prompt injection
  • Jailbreaking and guardrail bypass
  • Data exfiltration attempts
  • Model inversion and evasion techniques
  • RAG manipulation
  • Develop scripts and tooling to automate attack scenarios
  • Analyse model behaviour under adversarial pressure
  • Identify systemic vulnerabilities in:
  • APIs
  • Embedding pipelines
  • Vector databases
  • Fine-tuned model implementations
  • Collaborate with engineering teams to validate remediation
  • Document findings clearly and concisely

You will help ensure AI systems are resilient before they are deployed at scale.

Requirements

What We’re Looking ForCore Technical Skills
  • Strong experience in adversarial ML or AI security research
  • Experience working with LLM-based systems (OpenAI, Anthropic, open-source models, etc.)
  • Deep understanding of:
  • Prompt injection techniques
  • Model jailbreak methodologies
  • AI system exploitation vectors
  • Strong Python skills
  • Experience building custom attack tooling or experimentation frameworks
AI Systems Knowledge
  • Familiarity with:
    • RAG architectures
    • Vector databases
    • Model fine-tuning workflows
    • API-based model deployments
    • Understanding of model safety mechanisms and guardrails
Nice to Have
  • Background in cybersecurity or penetration testing
  • Familiarity with OWASP LLM Top 10
  • Experience working in enterprise environments
Who You Are
  • Curious and relentless
  • Comfortable thinking like an attacker
  • Creative in finding non-obvious vulnerabilities
  • Detail-oriented but fast-moving
  • Comfortable operating in ambiguity
  • Independent but collaborative

You don’t just run test cases — you design new ones.

Benefits

  • Comprehensive Private Medical Coverage
  • Support for Mental Health Expenses
  • Life Insurance Options
  • Attractive Compensation Package