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Pinecone Vector Databases Jobs in Washington (NOW HIRING)

Merican

AWS AI Engineer

Herndon, VA · On-site

Manage and optimize vector databases (e.g., Pinecone, Weaviate, Milvus) * Design and optimize Retrieval-Augmented Generation (RAG) pipelines for performance and scalability * Implement AI governance ...

Amivero

AI Engineer

Reston, VA

$75K - $190K/yr

Work with vector databases such as OpenSearch, Pinecone, Weaviate, Chroma, FAISS, or similar technologies for scalable retrieval systems. * Develop data ingestion and knowledge management pipelines ...

Amivero

AI Engineer

Reston, VA · On-site

$75K - $190K/yr

Work with vector databases such as OpenSearch, Pinecone, Weaviate, Chroma, FAISS, or similar technologies for scalable retrieval systems. * Develop data ingestion and knowledge management pipelines ...

Amivero

AI Engineer

Reston, VA

Work with vector databases such as OpenSearch, Pinecone, Weaviate, Chroma, FAISS, or similar technologies for scalable retrieval systems. * Develop data ingestion and knowledge management pipelines ...

Tekcel8

Gen AI

Washington, DC · On-site

... Vector Databases such as Pinecone, ChromaDB, FAISS, Weaviate, or Milvus · Experience integrating AI models through REST APIs · Strong understanding of embeddings, tokenization, and semantic search ...

Frontier Technology Inc.

AI/ML Engineer

Washington, DC · Remote

$190K - $220K/yr

Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid). * Write clean, efficient Python code for data ingestion, feature ...

Frontier Technology Inc.

AI/ML Engineer

Washington, DC · Remote

$190K - $220K/yr

Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid). * Write clean, efficient Python code for data ingestion, feature ...

Tata Consultancy Service Limited

Engineer

Mclean, VA · On-site

$100K - $120K/yr

... using vector databases (Pinecone, FAISS, Chroma DB, Azure AI Search) to enable enterprise-grade QA and summarization systems. • Integrate GenAI models into applications via APIs, SDKs ...

Tata Consultancy Service Limited

Engineer

Mclean, VA · On-site

$100K - $120K/yr

... using vector databases (Pinecone, FAISS, Chroma DB, Azure AI Search) to enable enterprise-grade QA and summarization systems. • Integrate GenAI models into applications via APIs, SDKs ...

SES

Gen AI/Python Developer - JL

Reston, VA · On-site

$52.25 - $72/hr

Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG). Exposure to data visualization tools (e.g., Power BI, Tableau). Bachelor s degree in Computer ...

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Pinecone Vector Databases information

What is a Pinecone Vector Database?

A Pinecone Vector Database is a cloud-based service designed to efficiently store, index, and search high-dimensional vector data, such as embeddings generated by machine learning models. It enables fast similarity search, making it ideal for use cases like semantic search, recommendation systems, and AI-powered applications. Pinecone handles the complexity of scaling and managing vector data, so developers can focus on building intelligent applications without worrying about infrastructure.

What are the key skills and qualifications needed to thrive as a Pinecone Vector Database Engineer, and why are they important?

To thrive as a Pinecone Vector Database Engineer, you need a strong background in computer science, data engineering, and experience with large-scale distributed systems, often supported by a relevant degree or equivalent experience. Proficiency in Python, REST APIs, cloud platforms (AWS, GCP), and vector search technologies, along with familiarity with Pinecone’s SDK and database management, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with cross-functional teams and deliver scalable solutions. These skills ensure robust database performance, efficient data retrieval, and successful integration of vector search capabilities into real-world applications.

What are some common challenges faced by engineers working with Pinecone Vector Databases, and how can they be addressed?

Engineers working with Pinecone Vector Databases often encounter challenges such as optimizing vector search performance at scale, ensuring data consistency across distributed systems, and integrating the database with various machine learning pipelines. Addressing these challenges typically involves tuning indexing parameters, monitoring resource utilization, and collaborating closely with data scientists to understand retrieval requirements. Regularly reviewing documentation and participating in community forums can also help engineers stay current with best practices and new features.

What is the difference between Pinecone Vector Databases vs Data Engineers?

AspectPinecone Vector DatabasesData Engineers
Primary RoleManaging and deploying vector database solutions for AI/ML applicationsDesigning, building, and maintaining data pipelines and infrastructure
Skills & CertificationsKnowledge of vector databases, cloud platforms, programming (Python, SQL)Data modeling, ETL processes, cloud services, programming (Python, Java)
Work EnvironmentTech companies, AI startups, cloud providersData-driven organizations, tech firms, finance, healthcare

While Pinecone Vector Databases specialists focus on deploying and managing vector database solutions for AI applications, Data Engineers build and maintain the data infrastructure that supports these systems. Both roles require programming skills and familiarity with cloud platforms, but their core responsibilities differ: one centers on database management, the other on data pipeline development.

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Pinecone Vector Databases jobs near you
AWS AI Engineer

AWS AI Engineer

Merican

Herndon, VA • On-site

Full-time

Posted 24 days ago

Job description

Role: AWS AI Engineer
Location: Herndon, VA
Work Mode: Onsite
About the Role
We are seeking a highly skilled AWS AI Engineer with strong hands-on experience in Kubernetes, EKS, and Generative AI systems. The ideal candidate will have deep expertise in deploying, scaling, and maintaining AI/ML workloads in production environments, along with experience in modern AI frameworks and platform engineering.
Certification Requirements (At least one required)
  • Active AWS Solutions Architect Certification
  • AWS Certified AI Foundations or AWS Certified AI Professional
  • Certified Kubernetes Administrator (CKA) - Active certification
Key Responsibilities
  • Deploy, manage, and troubleshoot Kubernetes clusters, including disconnected installations
  • Design, deploy, and upgrade Amazon EKS clusters in production environments
  • Perform advanced troubleshooting for EKS and Kubernetes-based systems
  • Implement and manage LLMOps workflows, including deployment, monitoring, and scaling of Generative AI systems
  • Build and maintain agent-based workflows using frameworks like LangChain, CrewAI, or AutoGen
  • Manage and optimize vector databases (e.g., Pinecone, Weaviate, Milvus)
  • Design and optimize Retrieval-Augmented Generation (RAG) pipelines for performance and scalability
  • Implement AI governance frameworks, including security guardrails and cost optimization strategies
  • Build and support Internal Developer Platforms (IDP) for AI use cases
Must-Have Skills
  • Strong Kubernetes expertise (installation, administration, troubleshooting)
  • Extensive hands-on experience with Amazon EKS (deployment, upgrades, troubleshooting)
  • Proven experience with LLMOps and production-grade Generative AI systems
  • Experience with agentic AI frameworks (LangChain, CrewAI, AutoGen)
  • Hands-on experience with vector databases and RAG architectures
  • Knowledge of AI governance, security guardrails (e.g., NeMo Guardrails), and cost control for LLMs
  • Experience building AI-focused Internal Developer Platforms
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About Merican

Sourced by ZipRecruiter

Merican is a IT Service consulting firm, specialized in Digital adoption and Business automation. With our diverse collection of skilled and committed consultants, technology companies, businesses and digital experts, we provide our subject expertise and our unique client service approach, a best-in-class global model of delivery suited to the business demands of our clients. We ensure that we implement future-oriented solutions for our clients via investments in people, solutions, technologies, competencies and infrastructure.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Columbia , MD, US

Year founded

2020

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