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

Photon

Data Lead- Dallas, TX

Dallas, TX · On-site

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 ...

Photon

Python developer - Dallas, Tx

Dallas, TX · On-site

$49.75 - $68.50/hr

Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus. * Strong proficiency in PostgreSQL, MySQL, MongoDB, Redis, and database optimization techniques . * Experience with ...

Photon

Python developer - Dallas, Tx

Dallas, TX · On-site

$49.75 - $68.50/hr

Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus. * Strong proficiency in PostgreSQL, MySQL, MongoDB, Redis, and database optimization techniques . * Experience with ...

Photon

Python Developer Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus. * Proficiency in relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis). * Experience with cloud ...

Photon

Python Developer Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus. * Proficiency in relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis). * Experience with cloud ...

BI Solutions Inc

WatsonX Assistant

Coppell, TX · On-site

... vector databases (PGVector, Vertex Matching Engine, Pinecone), Familiarity with Kafka or Pub/Sub eventing patterns. Observability stacks: OpenTelemetry, PrometheGrafana, Elk/Cloud Logging ...

Photon

Python Developer with ML - Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

... vector databases (e.g., Pinecone, Weaviate) for efficient storage and retrieval of high-dimensional vector embeddings to support RAG and semantic search functionalities. • Collaborate with AI ...

Ideate Technologies LLC

AI Engineer

Plano, TX · On-site

Experience with vector databases such as Pinecone, FAISS, or ChromaDB . * Experience with cloud platforms, preferably AWS . * Familiarity with Docker, Kubernetes, and CI/CD pipelines. * Strong ...

New

Marencor

Data Scientist with Python

Dallas, TX · On-site

... 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 ...

Photon

Senior Java Developer - AI/ML

Dallas, TX · On-site

$119K - $155K/yr

Cassandra Vector Databases * Pinecone * ChromaDB * Weaviate * Milvus * PGVector Cloud & DevOps Develop and deploy applications using: Cloud Platforms * AWS * Azure * Google Cloud Platform Services

Photon

Backend Lead - Python - Dallas, TX

Dallas, TX · On-site

Oversee the integration of Vector Databases (e.g., Pinecone, Weaviate, or PGVector) and design "memory" systems that allow agents to retain context across sessions. * Observability & Tracing:

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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.

What job categories do people searching Pinecone Vector Databases jobs in Allen, TX look for? The top searched job categories for Pinecone Vector Databases jobs in Allen, TX are:
What cities near Allen, TX are hiring for Pinecone Vector Databases jobs? Cities near Allen, TX with the most Pinecone Vector Databases job openings:
Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in Allen, TX as of August 2026, with employment types broken down into 87% Full Time, 5% Part Time, 1% Temporary, and 7% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.

Data Lead- Dallas, TX

Photon

Dallas, TX • On-site

Full-time, Contractor

Medical, Dental, Vision, Retirement, PTO

Re-posted 25 days ago

Job description


We are seeking a Lead Data Engineer to build and scale the data infrastructure powering our Agentic AI products. You will be responsible for the "Ingestion-to-Insight" pipeline that allows autonomous agents to access, search, and reason over vast amounts of proprietary and public data.
Your role is critical: you will design the RAG (Retrieval-Augmented Generation) architectures and data pipelines that ensure our agents have the right context at the right time to make accurate decisions.
Key Responsibilities
  • AI-Ready Data Pipelines: Design and implement scalable ETL/ELT pipelines that process both structured (SQL, logs) and unstructured (PDFs, emails, docs) data specifically for LLM consumption.
  • 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 & Embedding Strategies: Collaborate with AI Engineers to optimize data chunking strategies and embedding models to improve the "recall" and "precision" of the agent's knowledge retrieval.
  • Data Quality for AI: Develop automated "Data Cleaning" workflows to remove noise, PII (Personally Identifiable Information), and toxicity from training/context datasets.
  • Metadata Engineering: Enrich raw data with advanced metadata tagging to help agents filter and prioritize information during multi-step reasoning tasks.
  • Real-time Data Streaming: Build low-latency data streams (using Kafka or Flink) to provide agents with "fresh" data, enabling them to act on real-time market or operational changes.
  • Evaluation Frameworks: Construct "Gold Datasets" and versioned data snapshots to help the team benchmark agent performance over time.

Required Skills & Qualifications
  • Experience: 10+ years in Data Engineering, with at least 2 years focusing on data for LLMs or AI/ML applications.
  • Python Mastery: Deep expertise in Python (Pandas, Pydantic, FastAPI) for data manipulation and API integration.
  • Data Tooling: Strong experience with modern data stack tools (e.g., dbt, Airflow, Dagster, Snowflake, or Databricks).
  • Vector Expertise: Hands-on experience with at least one major Vector Database and knowledge of similarity search algorithms (HNSW, Cosine Similarity).
  • Search Knowledge: Familiarity with hybrid search techniques (combining semantic search with traditional keyword search like Elasticsearch/BM25).
  • Cloud Infrastructure: Proficiency in managing data workloads on AWS, Azure, or GCP.

Preferred Qualifications
  • Experience with LlamaIndex or LangChain for data ingestion.
  • Knowledge of Graph Databases (e.g., Neo4j) to help agents understand complex relationships between data points.
  • Familiarity with "Data-Centric AI" principles-prioritizing data quality over model size.

Compensation, Benefits and Duration
Minimum Compensation: USD 46,000
Maximum Compensation: USD 162,000
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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