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Entry Level Retrieval Augmented Generation Jobs in California

AI Engineer

Pleasanton, CA · On-site

$100K - $145K/yr

Design, develop, and deploy AI-driven solutions leveraging Retrieval-Augmented Generation (RAG), large language models (LLMs), and vector database technologies. * Build scalable clinical document ...

... retrieval-augmented generation (RAG) systems. • Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. • Help shape the future of AI ...

Experience orchestrating agentic workflows and retrieval augmented generation. Familiarity with LangGraph is a plus. * Stand up inference paths with low latency serving and token-level observability

Build and optimize retrieval-augmented generation (RAG) systems. * Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. * Help shape the ...

AI Engineer

San Francisco, CA · On-site

$120 - $190/hr

Familiarity with embeddings, vector databases, or retrieval augmented generation (RAG). * Experience deploying services in cloud environments (AWS, Azure, or GCP). * Interest in agentic AI ...

... retrieval-augmented generation (RAG) systems • Experience working with enterprise security and compliance frameworks (i.e., SOC 2, GDPR, etc.) • Familiarity with embeddings, vector databases and ...

... retrieval-augmented generation (RAG) systems • Experience working with enterprise security and compliance frameworks (e.g., SOC 2) • Familiarity with vector databases and large-scale document ...

Build and optimize retrieval-augmented generation (RAG) systems. * Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. * Help shape the ...

Build and optimize retrieval-augmented generation (RAG) systems. * Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. * Help shape the ...

Develop Retrieval Augmented Generation pipelines that provide relevant context from large document corpora to our design generation models. * Extract Delta Specifications : Parse customer change ...

New

Experience building or integrating retrieval-augmented generation (RAG) systems * Experience working with enterprise security and compliance frameworks (e.g., SOC 2) * Familiarity with vector ...

Experience building or integrating retrieval-augmented generation (RAG) systems * Experience working with enterprise security and compliance frameworks (e.g., SOC 2) * Familiarity with vector ...

Showing results 21-40

Entry Level Retrieval Augmented Generation information

What is an entry level retrieval augmented generation job?

Entry level retrieval augmented generation jobs involve assisting in the development and optimization of AI systems that combine information retrieval techniques with generative models. Employees in these roles typically help build, test, and maintain systems where AI retrieves relevant data from large databases to enhance the accuracy and relevance of generated responses. These positions often require basic skills in programming, machine learning, and familiarity with natural language processing. They are ideal for recent graduates or those new to AI, offering opportunities to learn about modern AI architectures and contribute to innovative projects. Entry level workers may work under the guidance of senior engineers or researchers, supporting experimentation and evaluation tasks.

What are the key skills and qualifications needed to thrive as an entry level retrieval augmented generation specialist?

To thrive as an Entry Level Retrieval Augmented Generation Specialist, you need a foundational understanding of natural language processing (NLP), information retrieval, and basic programming skills, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, vector databases (like FAISS or Pinecone), and frameworks for large language models (LLMs) is typically required. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate and troubleshoot solutions in team environments. These skills and qualities are crucial for building reliable RAG systems that deliver accurate and relevant information to users.

What are some common challenges faced by entry-level professionals working in retrieval augmented generation roles?

Entry-level professionals in Retrieval Augmented Generation (RAG) often encounter challenges such as understanding how to effectively combine information retrieval systems with large language models and adapting to rapidly evolving technologies. Balancing accuracy and efficiency when designing or fine-tuning retrieval pipelines can also be a learning curve. Additionally, you may need to collaborate closely with data engineers, machine learning specialists, and product teams to ensure the RAG system aligns with business requirements. Staying proactive in learning and engaging with peers can help overcome these challenges and accelerate career growth.

What is the difference between Entry Level Retrieval Augmented Generation vs Entry Level Data Scientist?

AspectEntry Level Retrieval Augmented GenerationEntry Level Data Scientist
Required CredentialsBasic programming, understanding of NLP and AI conceptsBachelor's in Data Science, Computer Science, or related field
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, consulting
Industry UsageAI development, NLP applications, chatbot creationData analysis, predictive modeling, data-driven decision making

Entry Level Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with generative AI, requiring knowledge of NLP and programming. Entry Level Data Scientist involves analyzing data, building models, and deriving insights, often with a broader data analysis skill set. While both roles require technical skills, Retrieval Augmented Generation is more specialized in AI model development, whereas Data Scientists work across various data projects.

What are the most commonly searched types of Retrieval Augmented Generation jobs in California?

The most popular types of Retrieval Augmented Generation jobs in California are:

What job categories do people searching Entry Level Retrieval Augmented Generation jobs in California look for?

The top searched job categories for Entry Level Retrieval Augmented Generation jobs in California are:

What cities in California are hiring for Entry Level Retrieval Augmented Generation jobs?

Cities in California with the most Entry Level Retrieval Augmented Generation job openings:

Infographic showing various Entry Level Retrieval Augmented Generation job openings in California as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 100% In-person job distribution.

$100K - $145K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Cognizant rating

7.2

Company rating: 7.2 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

53rd of 72 rated business consultants


Job description

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AI Engineer
About the role
As an AI Engineer, you will make an impact by designing and delivering advanced AI solutions that improve operational efficiency, accuracy, and decision-making across healthcare and healthcare insurance functions. You will be a valued member of the AI & Analytics team and work collaboratively with data scientists, healthcare domain experts, product teams, and technology stakeholders to build innovative AI-powered solutions supporting Risk Adjustment, Revenue Cycle Management, and clinical intelligence initiatives.
In this role, you will:
  • Design, develop, and deploy AI-driven solutions leveraging Retrieval-Augmented Generation (RAG), large language models (LLMs), and vector database technologies.
  • Build scalable clinical document search and knowledge retrieval platforms capable of processing and analyzing large volumes of healthcare data and unstructured content.
  • Develop and optimize AI pipelines for document indexing, semantic search, data enrichment, classification, and healthcare analytics use cases.
  • Collaborate with product, business, and clinical stakeholders to translate business requirements into secure, scalable, and compliant AI solutions.
  • Drive continuous improvement in AI model performance, data quality, automation, observability, and operational excellence.
Work model
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We strive to provide flexibility wherever possible. Based on this role's business requirements, this is a remote position open to qualified applicants in the United States. This role requires candidates to work primarily within the Pacific Time Zone business hours to effectively support client, business, and delivery team collaboration. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
What you need to have to be considered
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
  • Strong experience designing and implementing AI solutions using Retrieval-Augmented Generation (RAG) frameworks and vector databases.
  • Hands-on experience building enterprise AI applications involving semantic search, knowledge retrieval, document intelligence, and large language models.
  • Experience with data preprocessing, data quality management, data sanitation, annotation, and labeling workflows.
  • Proven experience optimizing performance, scalability, and reliability of large-scale AI systems and applications.
  • Experience designing and supporting AI-powered document search solutions capable of handling high-volume datasets and unstructured content.
  • Knowledge of cloud-based AI and machine learning solutions, preferably within Microsoft Azure environments.
  • Understanding of healthcare data, healthcare insurance operations, and AI governance best practices.
  • Strong analytical, problem-solving, communication, and stakeholder management skills.
These will help you stand out
  • Experience supporting Risk Adjustment, Revenue Cycle Management (RCM), claims analytics, or healthcare payer operations.
  • Familiarity with healthcare compliance standards such as HIPAA, ICD coding, and healthcare data privacy requirements.
  • Experience with Azure AI services, Azure OpenAI, Azure Machine Learning, or related cloud-native AI platforms.
  • Knowledge of vector database technologies, semantic search architectures, and enterprise knowledge management solutions.
  • Experience designing user interfaces, dashboards, and AI-driven business applications.
  • Experience developing generative AI solutions within highly regulated healthcare environments.

We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
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Salary and Other Compensation:
Applications will be accepted until August 21.2026.
The annual salary for this position is between $100,000- $145,000 USD depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
  • Medical/Dental/Vision/Life Insurance
  • Paid holidays plus Paid Time Off
  • 401(k) plan and contributions
  • Long-term/Short-term Disability
  • Paid Parental Leave
  • Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization's unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

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