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

Cna

Senior Data AI Engineer

Chicago, IL

$109K - $148K/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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Raks Group

QA Engineer with Gen AI

Chicago, IL

Understanding of prompt engineering, RAG (retrieval-augmented generation), and vector databases (e.g., Pinecone, Weaviate, Chroma). * Solid understanding of Agile/Scrum practices.

Eisneramper Llp

AI Solution Architect

Chicago, IL · On-site +1

$65 - $85.50/hr

Vector Databases: Azure Cosmos DB, Pinecone, or Weaviate * DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes About EisnerAmper: EisnerAmper is one of the largest accounting, tax, and ...

Lindsay & Brownell

AI Solution Architect

Chicago, IL · On-site +1

$65 - $85.50/hr

Vector Databases: Azure Cosmos DB, Pinecone, or Weaviate * DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes About EisnerAmper: EisnerAmper is one of the largest accounting, tax, and ...

Snowflake

Senior Solution Engineer

Chicago, IL · On-site

$165K - $216K/yr

Exposure to vector databases or semantic search tooling (e.g., Pinecone, Weaviate, pgvector) * Background in a technical presales or solutions engineering role at an AI/ML or data platform company ...

Innova Solutions, Inc

AI Solutions Architect

Chicago, IL · On-site

$180K - $190K/yr

Vector Databases (OpenSearch, Pinecone, Weaviate, Chroma, FAISS) * AI Governance, Responsible AI, Model Monitoring, and Security * Machine Learning & MLOps practices, including model lifecycle ...

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All JobsPinecone Vector Databases JobsPinecone Vector Databases Jobs in Elgin, 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 Elgin, IL? For Pinecone Vector Databases jobs in Elgin, IL, the most frequently searched job titles are:
What job categories do people searching Pinecone Vector Databases jobs in Elgin, IL look for? The top searched job categories for Pinecone Vector Databases jobs in Elgin, IL are:
What cities near Elgin, IL are hiring for Pinecone Vector Databases jobs? Cities near Elgin, IL with the most Pinecone Vector Databases job openings:
Pinecone Vector Databases jobs near you

Senior Data AI Engineer

Cna

Chicago, IL

$109K - $148K/yr

Full-time

Re-posted 19 days ago

Job description

You have a clear vision of where your career can go. And we have the leadership to help you get there.At CNA, we strive to create a culture in which people know they matter and are part of something important, ensuring the abilities of all employees are used to their fullest potential.

A senior individual contributor role responsible for designing, building, and operationalizing end-to-end AI and machine learning solutions that accelerate CNA's migration to a modern cloud data lakehouse. The engineer works across structured and unstructured data domains - including documents, images, audio, and transactional records - to unlock analytical value through scalable pipelines, RAG architectures, vector databases, and knowledge graphs. This role may also provide guidance to others to support the building of complex technical capabilities.

JOB DESCRIPTION:

Essential Duties & Responsibilities

Performs a combination of duties in accordance with departmental guidelines:

  • Design and build AI solutions that accelerate data migration from legacy systems to the cloud, ensuring scalability, reliability, and governance compliance.

  • Design and implement scalable ingestion and transformation pipelines across structured (SQL, relational) and unstructured (documents, images, audio, email, call transcripts) data sources, applying OCR, NLP preprocessing, and document chunking strategiesoptimizedfor LLM consumption.

  • Implement modernlakehousepatterns on Google Cloud Platform (GCP) - including data governance, cataloging, and lineage tracking - to ensure data is reliably discoverable, auditable, and fit for AI/ML workloads at scale.

  • Design and implement vector databases, embedding pipelines, and knowledge graph structures that serve as the foundational retrieval layer for RAG and other AI applications.

  • Productionize and operationalize AI solutions and advanced analytics in a DevOps/MLOpsenvironment, including automated testing, monitoring, and rollback capabilities.

  • Cultivate innovation by proactively proposingnew ideasandidentifyingthe right combination of tools and frameworks to turn business problems into analytics solutions.

  • Researches,identifiesand implements process improvements that address complex technology gaps. Builds strong knowledge of technology enablers.

May perform additional duties as assigned.

Reporting Relationship

Typically Director or above

Skills, Knowledge & Abilities

  • Deep expertise building scalable ingestion and transformation pipelines across structured and unstructured data sources; strong background migrating workloads from legacy systems to modern cloud platforms.

  • Skilled in parsing and normalizing diverse content types - PDFs, emails, images, and call transcripts - using OCR, NLP preprocessing (tokenization, entity extraction, summarization), and document chunking strategies optimized for LLM consumption.

  • 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 search applications

  • Strong SQL and data analytical skills; experience building data marts and feature datasets for data science and ML applications.

  • Strong coding fluency in Python; hands-on experience with BigQuery, Claude Code, RAG architectures, LLMs, ADK, and prompt engineering techniques

  • Expertise in building ML platforms and data pipelines at scale; familiarity with major ML algorithms, deep learning, NLP, information retrieval, and data mining techniques

  • Experience with GCP services (Vertex AI, Dataflow, BigQuery, Cloud Run, Pub/Sub); comfort with distributed computing frameworks (Apache Spark, Dataproc) for large-scale data processing.

  • Solid experience managing diverse data sources including preprocessing, cleansing, and verifying data integrity to meet data science and ML requirements

  • Demonstrated experience with machine learning, deep learning, information retrieval, NLP, or data mining - particularly applied to unstructured or semi-structured data

  • Hands-on experience with vector databases, embedding models (e.g., text-embedding-gecko, OpenAI Ada, Cohere), and end-to-end RAG pipeline design

  • Experience using Agile methods preferred.

  • Strong communication and interpersonal skills and the ability to work effectively with peers and team members in a highly matrixed environment.

  • Preferred experience with the insurance industry, its products and services.

  • Experience in implementing big data processing technology. Apache Spark preferred.

Education & Experience

  • Bachelor's Degree in Computer Science, Engineering, Mathematics, Computational Statistics, Data Science, or a related technical field (or equivalent experience);Master's Degreepreferred.

  • Typically7+ years of experience in data engineering, ArtificialIntelligenceor Machine Learning.

  • 2+ years of codingproficiencyin at least one programming language (Python, Java, SQL).

  • Applicable certifications preferred (GCP, Data Engineering).

#LI-KJ1 #LI-HYBRID

In certain jurisdictions, CNA is legally required to include a reasonable estimate of the compensation for this role. In District of Columbia, California, Colorado, Connecticut, Illinois, Maryland, Massachusetts, New York and Washington, the national base pay range for this job level is $72,000 to $141,000 annually.Salary determinations are based on various factors, including but not limited to, relevant work experience, skills, certifications and location. CNA offers a comprehensive and competitive benefits package to help our employees - and their family members - achieve their physical, financial, emotional and social wellbeing goals. For a detailed look at CNA's benefits, please visitcnabenefits.com.


CNAutilizesAI-enabled technology during the recruiting process. For more information, please visitourcareers page.


CNA is committed to providing reasonable accommodations to qualified individuals with disabilities in the recruitment process. To request an accommodation, please contactleaveadministration@cna.com

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