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

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 ...

Data Architect, Next Platform

Chicago, IL · On-site +1

$150K - $200K/yr

Experience with Vector databases (e.g., Pinecone, Weaviate, or pgvector) or Graph databases to support RAG and agentic memory. * Cloud Architecture: Hands-on experience with GCP (BigQuery, Vertex AI ...

Data Architect, Next Platform

Chicago, IL · On-site

$150K - $200K/yr

Experience with Vector databases (e.g., Pinecone, Weaviate, or pgvector) or Graph databases to support RAG and agentic memory. * Cloud Architecture: Hands-on experience with GCP (BigQuery, Vertex AI ...

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

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 ...

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 ...

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 ...

Showing results 21-40

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 cities near Elgin, IL are hiring for Pinecone Vector Databases jobs?

Cities near Elgin, IL with the most Pinecone Vector Databases job openings:

Managing Solution Architect

Capgemini

Chicago, IL • On-site

$65 - $85.50/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 days ago


Capgemini North America rating

7.7

Company rating: 7.7 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

98th of 224 rated it services


Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Location
Chicago, IL; Atlanta, GA; New York, NY; Dallas, TX; San Francisco, CA
Your Role
We are seeking a highly technical, hands-on, and implementation-focused Solution Architect for Cloud, Data Analytics and AI In this role, your primary focus will be implementation and end-to-end technical execution. You will be the solution architect, designing architecture blueprints suggesting right fit technologies for solving complex technical asls from clients in areas of Data, Cloud and AI. You will be guiding team to write code, build prototypes, and directly guiding development teams to turn complex system designs into stable, scalable production grade solutions.
Key Responsibilities
  • Drive the day-to-day coding, technical builds, and engineering delivery of end-to-end data and AI platforms, working closely with Capgemini's development team and clients .
  • Partner directly with client delivery teams to execute complex platform migrations, cloud migrations, and tech-stack modernization projects across Data, Analytics, and AI domains. Hands on Knowledge of Gen AI is must. The candidate must be able to use Claude Code, Open AI Codex and Cursor.
  • Build, scale, and realize detailed enterprise blueprints, translating conceptual patterns like Data Lake Medallion, event-driven, domain-driven, and modular microservices into functional application stacks.
  • Support presales activities by creating rapid technical prototypes, conducting proof-of-concept (POC) builds, and architecting specific implementation pricing engines based on deep technical realities are required.
  • Collaborate directly with technical leads from our alliance ecosystem-such as AWS, Microsoft, Google, Snowflake, Databricks, and Anthropic to know their latest features.
  • Lead sprint teams from an engineering perspective, taking full ownership of deployment pipelines, complex environment configurations, and the real-time resolution of critical blockages during development phases.

Required skills and Expereince
  • Minimum of 14 years of experience in the IT industry.
  • Minimum of 6 years of dedicated experience acting in an Architecture capacity.
  • Industry awareness across one or more sectors is highly valued: Manufacturing, Automotive, Life Sciences, Telecommunications, Media, Hi-Tech, or Energy & Utilities.
  • Bachelor's or master's degree in computer science, Information Systems, or a closely related technology field

Technical Skills & Competencies
  • Expert-level, hands-on programming proficiency in Spark, Scala, and Java within major hyperscaler environments (AWS, Azure, or Google Cloud). Active, professional cloud certifications are highly desired.
  • Deep practical implementation experience with AI ecosystems like AWS Bedrock, AWS SageMaker, Google Vertex AI, Azure ML, and OpenAI. Mastery of building functional pipelines featuring prompt engineering, LLM fine-tuning, Agent Mesh, RAG, Vector Databases, Chain-of-Thought, Context Engineering, Loop Engineering, and MLOps/LLMOps. Direct facility with AI developer productivity toolsets (e.g., Cursor, Codex, Claude Code). While vibe coding knowledge is good to have, hands on implementation knowledge of LLM fine tuning, context engineering, Vector Databases Design, Model Routing, LLM Orchestration, Developing Agents and building Agentic Mesh, technologies such as LangChain, LlamaIndex, PineCone, Milvus, PyTorch, Tensor Flow and different transformer models including Claude, Gemini, OpenAI models, and ability to optimize token usage etc. are crucial for this role.
  • Strong data engineering experience with cross-platform analytical data warehouses and data lakes houses, specifically Python, Spark, Big Query, Redshift, Synapse, Databricks or Snowflake.
  • The candidate should have exposure to different styles of database modeling relational systems and modern NoSQL databases. Exposure or working knowledge in Graph database will be valuable.
  • Experience in developing microservices, event-driven platforms, and streaming/batch pipelines (Glue, Data Factory, DataFlow, Composer, Airflow, Kafka, Flink, or equivalent cloud services).
  • Experience in Data Governance tools for data quality, data lineage, observability, and data marshalling, with preference for practical tooling validation using Informatica, Alation, Collibra, or Reltio will be valuable.
  • Direct experience structuring real-world semantic layers, creating reusable data products, managing secure data shares, will be valuable.
  • Awareness about secure network layout, infrastructure security controls, fault-tolerant/resilient cloud architecture setups, and FinOps scripting for resource scaling and cost optimization will be valuable.
  • Deep fluency in DataOps, DevOps, and delivery pipeline automation, with direct hands-on configuration experience using GitHub Actions, Jenkins, Terraform, and git version management within fast-paced Agile environments are required

The base compensation range for this role in the posted location is $150,000- $210,000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

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