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Vector Database Job Jobs (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

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 ...

Expert Technology Services

AI ML Engineer

Lakeland, FL · On-site

RAG + vector database expertise * Infrastructure + performance optimization (GPU / Kubernetes) Required Skills : * Local-First AI Expertise: Proven track record deploying and optimizing open-source ...

Geisinger Health

Senior Platform Data Engineer

Danville, PA · On-site +1

$121K - $164K/yr

Administers the vector database: schema design, indexing, metadata management, access controls, and performance tuning. * Builds and maintains retrieval pipelines: hybrid search (vector + keyword ...

Accenture Federal Services

AI Engineer

Washington, DC · On-site

Work across technologies such as AWS Bedrock, Databricks, vector databases, and advanced promptengineering techniques. * Build agent frameworks supporting scientific discovery in areas like ...

LCG Inc

Full Stack Developer, Associate

Bethesda, MD · On-site

Implement semantic search and document retrieval systems using vector databases to support AI-driven knowledge retrieval. * Enhance and maintain the existing client AI Chat Tool, improving user ...

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As of Jul 7, 2026, the average hourly pay for vector database job in the United States is $32.20, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $39.42 per hour, depending on experience, location, and employer.
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Data Lead- Dallas, TX

Data Lead- Dallas, TX

Photon

Dallas, TX • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Posted 23 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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