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Qdrant Jobs in Missouri (NOW HIRING)

Jobtailor

AI Software Engineer

Dearborn, MO · On-site

$110 - $150/hr

Experience with vector search, hybrid retrieval architectures, or vector databases (Chroma, Qdrant, Pinecone, pgvector). * Experience working with GCP services (Vertex AI, Cloud Run, and BigQuery) or ...

New

Merck Group

Staff Software Engineer

Saint Louis, MO · On-site

$110K - $165K/yr

Vector Databases like Qdrant Nice to have Skills: * Experience with Kubernetes and container orchestration. * Familiarity with event-driven architectures and messaging platforms such as Kafka.

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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.

What are popular job titles related to Qdrant jobs in Missouri? For Qdrant jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Qdrant jobs in Missouri look for? The top searched job categories for Qdrant jobs in Missouri are:
What cities in Missouri are hiring for Qdrant jobs? Cities in Missouri with the most Qdrant job openings:
Qdrant jobs near you
Infographic showing various Qdrant job openings in Missouri as of August 2026, with employment types broken down into 88% Full Time, 1% Part Time, and 11% Contract. Highlights an 67% Physical, 5% Hybrid, and 28% Remote job distribution.

AI Software Engineer

Jobtailor

Dearborn, MO • On-site

$110 - $150/hr

Other

Posted 3 days ago

New

Job description

Responsibilities
  • Design and Build Agentic Workflows: Design and build AI-powered applications, agents, and intelligent workflows that improve discovery, recommendation, and analysis of marketing enterprise analytics assets, customer data, and media metrics.
  • Architect Autonomous Loops: Transition from linear "chain" workflows to self-correcting agentic loops using frameworks like LangChain, LangGraph, or LlamaIndex to automate complex marketing analytics workflows.
  • Implement Tool-Use & MCP: Design and implement robust "tool-calling" capabilities, ensuring LLMs can reliably interact with external marketing APIs, Customer Data Platforms (CDPs), and internal media databases. Build and maintain Model Context Protocol (MCP) servers to bridge the gap between LLMs and our proprietary marketing data silos securely and in real-time.
  • Develop High-Concurrency Backends: Develop asynchronous Python (FastAPI/Flask) or Java (Spring Boot) backend services optimized for long-running AI tasks, marketing attribution modeling, and real-time token streaming.
  • Build Streaming Frontends: Build responsive, stateful UIs in React or Angular that handle complex AI interactions (streaming text, generative UI components, and multi-modal feedback).
  • Optimize Advanced RAG Pipelines: Implement advanced RAG pipelines (re-ranking, query transformation, and embedding optimization) to maximize retrieval precision over vast libraries of marketing assets, creative guidelines, and historical campaign results.
  • Establish AI Evals & Observability: Establish AI Evals to quantify hallucination rates, latency, and cost, leading the shift from "vibes-based" testing to rigorous, automated AI benchmarking.
  • Collaborate & Guide: Collaborate with product managers, marketing experts, and domain stakeholders to translate business needs into technical solutions. Drive architecture decisions, engineering best practices, and operational excellence.
Requirements
  • Masters Degree in Computer Science, Information Systems, or a related quantitative field.
  • 3+ years of professional experience in Software Engineering or Data Science building scalable production systems.
  • 1+ years of hands-on experience designing, training, and deploying complex AI/ML systems in production environments.
  • Experience working with Python, Java, JavaScript, or Angular programming languages.
  • Experience in building autonomous agents using agent orchestration frameworks such as LangGraph, LangChain, LlamaIndex, or similar technologies.
  • Experience implementing tool integration patterns (MCP), agent communication protocols, and AI application observability.
  • Experience with vector search, hybrid retrieval architectures, or vector databases (Chroma, Qdrant, Pinecone, pgvector).
  • Experience working with GCP services (Vertex AI, Cloud Run, and BigQuery) or similar cloud platforms for deploying scalable AI solutions.
  • Strong problem-solving and system design skills with the ability to evaluate competing technical approaches and articulate tradeoffs.
  • Solid understanding of data engineering (SQL, Spark, data pipelines) and a strong interest or experience in quantitative marketing concepts like multi-touch attribution, cohort analysis, and predictive customer lifetime value.
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