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Pinecone Vector Databases Jobs in Dallas, TX (NOW HIRING)

CCS INC

AI/ML Engineer

Plano, TX · On-site

$65 - $75/hr

Deep operational expertise with vector databases, such as Pinecone, Milvus, Weaviate, or Qdrant. * AWS Solutions Architect, AWS DevOps Engineer, or equivalent industry certifications.

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Senior Staff Data Engineer - Python / Google Cloud

Dallas, TX · Remote

$160K - $190K/yr

Design and optimize the storage of embeddings in Vector Databases (e.g., Pinecone, ChromaDB, Vertex AI Search) and Graph Databases (e.g., FalkorDB, Neo4j) to enable multi-step agentic reasoning ...

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CCS INC

Gen AI Engineer

Plano, TX · On-site

$40 - $50/hr

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). * Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)

CCS INC

Lead Gen AI Engineer

Plano, TX · On-site

$85 - $110/hr

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate). * Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)

Precision Technologies Corp

Sr. Data/GenAI Engineer

Irving, TX · On-site

$101K - $138K/yr

... vector databases (e.g., Pinecone, Chroma, PGvector) and the concept of embeddings. o Experience working with a variety of data sources, from structured databases to semi-structured API outputs. o ...

INFOSYS NOVA HOLDINGS LLC

Gen. AI Engineer

Fort Worth, TX · On-site

$100K - $160K/yr

Experience building Retrieval-Augmented Generation (RAG) solutions and working with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search. * Experience with Agentic AI ...

ClifyX

Java Full stack Engineer

Irving, TX · On-site

Architect and optimize production-grade Retrieval-Augmented Generation (RAG) pipelines, focusing on advanced embedding strategies, efficient vector database management (Pinecone, Milvus, Chroma), and ...

Vytwo

GenAI & Agentic AI Engineer

Prosper, TX · On-site

Work with vector databases (FAISS, Pinecone, Chroma, Weaviate) for semantic search. * Monitor, evaluate, and optimize GenAI models for accuracy, performance, and cost. Expertise You'll Bring: * 5+ ...

Marencor

Python Developer

Dallas, TX · On-site

$49.75 - $68.50/hr

... vector databases such as MongoDB Atlas or Pinecone * Portfolio of LLM applications and sample projects * 2+ years of NLP experience using tools such as NLTK, SpaCy, and Beautiful Soup * 1+ years of ...

Wells Fargo

Senior Specialty AI Engineer

Irving, TX · Hybrid

$117K - $155K/yr

Configure and manage vector databases (e.g., Pinecone, Weaviate, FAISS). Vertex AI & Cloud Engineering * Develop and deploy services using Google Vertex AI (model endpoints, pipelines, vector search ...

BI Solutions Inc

Senior Agentic AI Developer

Coppell, TX · On-site

$50.75 - $67/hr

Experience with RAG architectures, embeddings, vector databases (Pinecone, Weaviate, Chroma, pgVector), prompt engineering, and AI orchestration. * Hands-on experience with AI development tools such ...

Photon

Data Engineer - Dallas, TX

Dallas, TX · On-site

$113K - $136K/yr

Vector Database Management: Architect and optimize Vector Databases (e.g., Pinecone, Weaviate, Milvus, or Qdrant) to ensure high-speed, relevant similarity searches for agentic retrieval. * Chunking ...

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All JobsPinecone Vector Databases JobsPinecone Vector Databases Jobs in Dallas, TX

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.

What are popular job titles related to Pinecone Vector Databases jobs in Dallas, TX?

For Pinecone Vector Databases jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Pinecone Vector Databases jobs in Dallas, TX look for?

The top searched job categories for Pinecone Vector Databases jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Pinecone Vector Databases jobs?

Cities near Dallas, TX with the most Pinecone Vector Databases job openings:

Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in Dallas, TX as of August 2026, with employment types broken down into 88% Full Time, 5% Part Time, 1% Temporary, and 6% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution.

AI/ML Engineer

CCS INC

Plano, TX • On-site

$65 - $75/hr

Full-time

Medical, Dental, Vision

Re-posted 24 days ago

Job description

Benefits:
  • Bonus based on performance
  • Dental insurance
  • Health insurance
  • Vision insurance

Qualifications
  • Bachelor’s Degree 
  • 6+ years cloud architecture experience
  • 3+ years building production GenAI/LLM systems on AWS.  
  • Strong Python and AWS expertise, including Lambda, ECS/EKS, S3, SageMaker, Docker and Kubernetes.  
  • Production experience with vector databases and designing ingestion + embedding pipelines for both batch and streaming workloads.  
  • Hands-on with prompt design, evaluation, LLM orchestration, and RAG implementation patterns.  
  • Experience deploying and operating model- serving or MCP – like server infrastructure (selfhosted or managed).  
  • Proficient with IaC and delivery tooling, including Terraform/CloudFormation, GitOps, and CI pipelines.  
  • Experience with model-serving infrastructure, such as Amazon SageMaker, NVIDIA Triton, Ray Serve, or similar platforms.  
  • Hands-on experience with GenAI libraries and frameworks, including LangChain, LlamaIndex, Hugging Face, and OpenAI APIs.  
  • Deep operational expertise with vector databases, such as Pinecone, Milvus, Weaviate, or Qdrant.  
  • AWS Solutions Architect, AWS DevOps Engineer, or equivalent industry certifications. 
 
Responsibilities
  • Cloud Architecture & Infrastructure, Design scalable, secure AWS architectures
  • LLM & GenAI Platforms, Lead integration of API-based and self-hosted LLMs, implement RAG solutions
  • Prompting & Evaluation, Develop prompt engineering strategies, reusable templates, and evaluation frameworks 
  • Vector Databases & Retrieval Pipelines, Implement and maintain vector stores (OpenSearch, Pinecone, Milvus, Qdrant) 
  • Data Ingestion & Processing Pipelines 
  • Microservices & Serverless Systems 
  • Python Development & AI Tooling 
  • Security, Governance & Cross-Functional Leadership