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Pinecone Vector Databases Jobs in Chicago, IL (NOW HIRING)

9to9 Software Solutions LLC

AI Lead

Chicago, IL · On-site

$144K - $177K/yr

... of vector databases like Pinecone, FAISS, or Weaviate. · Experience with Azure SQL, CosmosDB, and scalable backend architecture. · Familiarity with LangChain, LLamaIndex, and Microsoft Semantic ...

CNA

Senior Data AI Engineer

Chicago, IL · On-site

$118K - $141K/yr

Proven experience designing and implementing vector databases (e.g., Vertex AI Vector Search, Pinecone, pgvector), embedding pipelines, and knowledge graph structures that underpin RAG and semantic ...

Tekcel8

Gen AI

Chicago, IL · On-site

... Vector Databases such as Pinecone, ChromaDB, FAISS, Weaviate, or Milvus · Experience integrating AI models through REST APIs · Strong understanding of embeddings, tokenization, and semantic search ...

GState Consulting LLC

AI Engineer

Chicago, IL · On-site

Familiarity with vector databases like Pinecone, Chroma, Weaviate, or FAISS. * Experience developing REST APIs or microservices. * Hands-on experience with AWS, Azure, or Google Cloud Platform.

rSTAR Technologies LLC.

AI Architect

Westmont, IL · On-site

$63.50 - $82.75/hr

... of vector databases like Pinecone, FAISS, or Weaviate. · Experience with Azure SQL, CosmosDB, and scalable backend architecture. · Familiarity with LangChain, LLamaIndex, and Microsoft Semantic ...

Northern Base

Senior GenAI/Python Engineer

Chicago, IL · Remote

$124K - $167K/yr

... vector databases such as pgvector, Pinecone, Weaviate, OpenSearch, Snowflake Vector Functions, or equivalent technologies ✔ Strong API development experience using FastAPI, Flask, or Django ...

Morningstar

Senior Software Engineer

Chicago, IL · On-site +1

$153K/yr

Architecting, optimizing relational and vector databases (PostgreSQL, SQLAlchemy, query optimization, indexes, replicas, migrations, Weaviate, Pinecone) and working with dataframes for data ...

Morningstar, Inc.

Senior Software Engineer

Chicago, IL · On-site

$153K/yr

Architecting, optimizing relational and vector databases (PostgreSQL, SQLAlchemy, query optimization, indexes, replicas, migrations, Weaviate, Pinecone) and working with dataframes for data ...

GState Consulting LLC

AI Architect

Chicago, IL · On-site

$65 - $85.50/hr

Vector Databases (Pinecone, FAISS, Weaviate, ChromaDB) * Docker & Kubernetes * AWS / Azure / Google Cloud Platform * Git, CI/CD * SQL & NoSQL Databases Preferred Skills * MCP (Model Context Protocol)

Accenture

Knowledge Engineer - Back End

Chicago, IL · On-site

Minimum 3 years experience deploying and operating vector databases (e.g., Pinecone, Weaviate, Milvus, or Qdrant) in production environments. * Minimum 3 years Proficiency in Python or Java for ...

New

Capgemini

Managing Solution Architect

Chicago, IL · On-site

$65 - $85.50/hr

... Vector Databases Design, Model Routing, LLM Orchestration, Developing Agents and building Agentic Mesh, technologies such as LangChain, LlamaIndex, PineCone, Milvus, PyTorch, Tensor Flow and ...

Capgemini

Managing Solution Architect

Chicago, IL · On-site

$150 - $210/hr

... Vector Databases Design, Model Routing, LLM Orchestration, Developing Agents and building Agentic Mesh, technologies such as LangChain, LlamaIndex, PineCone, Milvus, PyTorch, Tensor Flow and ...

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All JobsPinecone Vector Databases JobsPinecone Vector Databases Jobs in Chicago, IL

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 are popular job titles related to Pinecone Vector Databases jobs in Chicago, IL? For Pinecone Vector Databases jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Pinecone Vector Databases jobs in Chicago, IL look for? The top searched job categories for Pinecone Vector Databases jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Pinecone Vector Databases jobs? Cities near Chicago, IL with the most Pinecone Vector Databases job openings:
Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in Chicago, IL 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.

Azure Developer (OpenAI & RAG Chatbot )

Snowrelic Inc

Deerfield, IL • Remote

$56.25 - $69.75/hr

Full-time

Re-posted 11 days ago

Job description

We are seeking an experienced Azure Developer with 2-3 years in OpenAI and 8-10 years in development, specializing in Python, FastAPI, and Azure AI Services. The role involves building and optimizing AI-driven chatbots, Retrieval-Augmented Generation (RAG) applications, and cloud-based AI solutions. 

Key Responsibilities 

  • AI & Chatbot Development: Design and deploy RAG-based chatbots using Azure OpenAI, Azure Cognitive Search, and Vector Databases. 

  • API Development: Develop and optimize APIs using FastAPI, integrating with OpenAI, Azure AI, and external systems. 

  • Azure Cloud Development: Implement AI solutions using Azure Functions, Cognitive Services, and Kubernetes (AKS). 

  • POC & Documentation: Rapidly develop POCs and ensure comprehensive documentation. 

  • Performance Optimization: Optimize AI models for efficiency and cost-effectiveness on Azure infrastructure. 

Key Skills 

  • Programming: Python (FastAPI preferred), C# (optional). 

  • Cloud & AI: Azure OpenAI, Cognitive Search, Bot Service, Machine Learning, Cognitive Services. 

  • Database & Search: Azure SQL, CosmosDB, Vector DBs (Pinecone, FAISS, Weaviate). 

  • DevOps & Security: Azure DevOps, Docker, Kubernetes, OAuth, JWT. 

  • Frameworks: LangChain, LLamaIndex, Semantic Kernel (preferred). 

Qualifications 

  • 8-10 years of software development experience with 2-3 years in OpenAI and RAG. 

  • Proven expertise in Azure AI Services and Python (FastAPI). 

  • Strong problem-solving skills, POC development, and ability to work with technical documentation.