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Qdrant Jobs in Virginia (NOW HIRING)

Python web/API development (FastAPI, Flask, Django) Local AI model stacks (vLLM, LiteLLM, Ollama); reverse proxies (Caddy, Nginx, Traefik); vector databases (pgvector, Qdrant, Milvus, Weaviate) LLM ...

AI & ML Engineer

Chantilly, VA · On-site

$99K - $225K/yr

Experience with vector databases such as Qdrant and relational databases such as Postgres * Experience with on-prem compute * Knowledge of MITRE ATT&CK framework Clearance: Applicants selected will ...

Experience with vector databases such as Qdrant and relational databases such as Postgres * Experience with on-prem compute * Knowledge of MITRE ATT&CK framework Clearance: Applicants selected will ...

AI & ML Engineer

Chantilly, VA · On-site

$99K - $225K/yr

Experience with vector databases such as Qdrant and relational databases such as Postgres * Experience with on-prem compute * Knowledge of MITRE ATT&CK framework Clearance: Applicants selected will ...

AI & ML Engineer

Chantilly, VA · On-site

$99K - $225K/yr

Experience with vector databases such as Qdrant and relational databases such as Postgres * Experience with on-prem compute * Knowledge of MITRE ATT&CK framework Clearance: Applicants selected will ...

Qdrant information

What is the difference between Qdrant vs Data Scientist?

AspectQdrantData Scientist
Required CredentialsTechnical certifications, knowledge of vector databasesDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, startups, AI-focused firmsResearch labs, tech companies, consulting firms
Industry UsageAI, machine learning, data storageData analysis, predictive modeling, research

Qdrant primarily focuses on managing and deploying vector similarity search databases, requiring technical skills in database management and AI tools. Data Scientists analyze data, build models, and interpret results. While both roles operate within the tech and AI industry, Qdrant specialists are more technical and infrastructure-oriented, whereas Data Scientists focus on data analysis and modeling.

What cities in Virginia are hiring for Qdrant jobs? Cities in Virginia with the most Qdrant job openings:
Infographic showing various Qdrant job openings in Virginia as of June 2026, with employment types broken down into 1% Internship, 92% Full Time, and 7% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution.

Agentic AI - Java Background

TechYantram Solutions

Arlington, VA • On-site

$66 - $84/hr

Other

Posted 24 days ago


Job description

Agentic AI - Java BackgroundIntroduction:

As a member of our Agentic AI team with a Java background, you will be responsible for developing and implementing innovative AI solutions using cutting-edge technologies. You will work closely with our team to create AI-powered applications that drive business growth and enhance user experiences.

Responsibilities:
  • Develop and deploy Java microservices using LangChain4j and Spring AI
  • Implement Semantic Kernel for enhanced AI capabilities
  • Utilize Retrieval-Augmented Generation (RAG) for advanced AI functionalities
  • Work with Milvus, Qdrant, and Pinecone for efficient data storage and retrieval
  • Integrate LLM (Large Language Model) for natural language processing tasks
  • Utilize Spring Boot and Spring Cloud for building scalable applications
  • Implement Hibernate for database management
  • Create and maintain RESTful APIs for seamless communication between services
  • Utilize PostgreSQL and NoSQL databases for data storage and retrieval
  • Work with Vector Databases, including PGVector and Chroma, for AI model storage
  • Implement messaging systems such as Kafka and RabbitMQ for real-time data processing
  • Utilize WebSockets for bidirectional communication between clients and servers
  • Deploy applications on cloud platforms such as AWS, Azure, and Google Cloud Platform
  • Containerize applications using Docker and manage container orchestration with Kubernetes
Requirements:

Required Skills:

  • Proficiency in Java programming
  • Experience with developing Java microservices
  • Knowledge of AI technologies such as RAG, LLM, and Semantic Kernel
  • Experience with Spring Boot, Spring Cloud, and Hibernate
  • Understanding of RESTful API design and implementation
  • Experience with PostgreSQL and NoSQL databases
  • Familiarity with Vector Databases like PGVector and Chroma
  • Experience with messaging systems such as Kafka and RabbitMQ
  • Knowledge of WebSockets for real-time communication
  • Experience with cloud platforms like AWS, Azure, and Google Cloud Platform
  • Proficiency in Docker and Kubernetes for containerization and orchestration

Preferred Skills:

  • Experience with Milvus, Qdrant, and Pinecone for data storage and retrieval