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Qdrant Jobs in Illinois (NOW HIRING)

Capgemini

Senior Software Engineer

Chicago, IL · On-site

$73K - $174K/yr

Experience working with vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or Azure AI Search. The base compensation range for this role in the posted location is: $73,150 to $174,000 ...

Qumis Inc

Founding Staff AI Engineer

Chicago, IL · On-site

$150K - $250K/yr

Deep experience with RAG pipelines, multi-step LLM workflows, and vector databases (e.g., Pinecone, Weaviate, Qdrant) * Comfortable working with complex, messy documents (e.g., insurance policies ...

Accenture

AI Native Transformation Manager

Chicago, IL · On-site

$117K - $120K/yr

Hands-on experience with vector databases and RAG architectures (Qdrant, Pinecone, ChromaDB, Weaviate) * Understanding of graph databases and knowledge graphs (Neo4j, Neptune) for semantic ...

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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.

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For Qdrant jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Qdrant jobs in Illinois look for?

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Qdrant jobs near you
Infographic showing various Qdrant job openings in Illinois as of August 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 57% Physical, 5% Hybrid, and 38% Remote job distribution.

AI Automation Developer

Everest Technologies

Chicago, IL • On-site

Other

Posted 5 days ago

Job description

We are seeking a hands-on Senior Full-Stack AI Engineer to design, build, and deploy production-grade AI-native applications. In this role, you will lead the integration of Large Language Models (LLMs), AI agent frameworks, and vector search systems into scalable web applications, bridging the gap between cutting-edge Generative AI features and robust full-stack software architecture.

Key Responsibilities

  • AI Systems Architecture & Engineering: Design and implement agentic AI workflows, LLM orchestration layers, and RAG (Retrieval-Augmented Generation) pipelines using frameworks such as LangChain, LlamaIndex, or AutoGen.

  • Backend Development: Build high-performance, asynchronous REST/gRPC APIs and microservices using Python (FastAPI/Flask) or Node.js to interface with vector databases (Pinecone, Qdrant, Chroma) and relational/NoSQL storage.

  • Frontend Integration: Implement modern UI components in React, Next.js, or Angular to deliver real-time streaming AI interfaces, interactive dashboards, and conversational workflows.

  • MLOps & Evaluation: Implement continuous LLM performance monitoring, prompt management/versioning, latency optimization, cost management, and automated evaluation pipelines for model outputs.

  • Cloud & DevOps: Deploy scalable, containerized microservices on AWS/Azure/Google Cloud Platform using Docker and Kubernetes, maintaining CI/CD pipelines and observability tools.

Required Skills & Qualifications

  • Experience: 5+ years in full-stack software engineering, with at least 2+ years dedicated to building and deploying production-level AI/GenAI applications.

  • AI & LLM Stack: Strong proficiency with OpenAI APIs, Anthropic Claude, open-source models (Hugging Face), vector databases, and agentic frameworks.

  • Core Tech Stack: Python (FastAPI), JavaScript/TypeScript (React, Next.js, Node.js), and database systems (PostgreSQL, MongoDB, Redis).

  • Software Engineering: Solid understanding of microservices, event-driven architectures, API security, and asynchronous programming.

  • Cloud & CI/CD: Hands-on experience with cloud platforms, preferably Azure, Docker, and modern CI/CD tools.

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