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Entry Level Retrieval Augmented Generation Jobs in Virginia

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

AI Evaluation Scientist

Mclean, VA · On-site

$105K - $145K/yr

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

AI Evaluation Scientist

Mclean, VA · On-site

$105K - $145K/yr

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

AI Evaluation Scientist

Mclean, VA · On-site

$105K - $145K/yr

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

AI Evaluation Scientist

Mclean, VA · On-site

$105K - $145K/yr

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

AI Evaluation Scientist

Mclean, VA · On-site

$105K - $145K/yr

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

AI Evaluation Scientist

Mclean, VA · On-site

$105K - $145K/yr

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

Build, optimize, and maintain production-grade Retrieval-Augmented Generation pipelines and semantic search systems. * Design and manage data preprocessing workflows, chunking strategies, and vector ...

AI Evaluation Scientist

Mclean, VA · On-site

$105K - $145K/yr

Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.

Showing results 41-60

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 Virginia?

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

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

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

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

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

Infographic showing various Entry Level Retrieval Augmented Generation job openings in Virginia as of August 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution.

$65 - $89/hr

Full-time

Re-posted 5 days ago


Job description

Freedom Technology Solutions Group is looking for a Cloud Solutions Architect to add to our growing team based out of Virginia! The ideal candidate has familiarity with the following skillsets: Programming Languages & Scripting / Cloud Platforms & Services / Systems Architecture & Engineering / Cybersecurity & Accreditation / Data Engineering & Analytics / Machine Learning & Data Science / Software Development & Tools / Enterprise IT & Endpoint Services / Documentation, Communication & Collaboration / Specialized Tools & Technologies.

Required Skills:

  1. An active security clearance with a polygraph.
  2. Proficiency in Python, Java, JavaScript, and shell scripting for automation and data processing tasks
  3. Experience with SQL, MySQL, and PostgreSQL for relational database development and querying
  4. Ability to work with structured and unstructured data formats including JSON and XML
  5. Familiarity with modern programming environments such as Visual Studio, WebStorm, and notebook-based development
  6. Hands-on experience designing and implementing secure, scalable cloud infrastructure in AWS, Azure, or GCP
  7. Proven ability to configure and maintain cloud services including EC2, S3, Lambda, VPC, and IAM roles
  8. Experience with cloud security best practices, including encryption, access control, and compliance frameworks
  9. Familiarity with multi-cloud networking, traffic engineering, and performance optimization across cloud platforms
  10. Demonstrated experience in systems architecture, virtualization (VMWare), and infrastructure deployment
  11. Ability to lead full lifecycle systems development including design, testing, and integration
  12. Familiarity with ICD 503 and A&A processes for secure system accreditation
  13. Experience with identity lifecycle management and enterprise IT integration
  14. Strong understanding of cybersecurity principles including DNS, routing, VPNs, and certificate authentication
  15. Experience supporting A&A workflows and implementing security controls across cloud and on-prem environments
  16. Familiarity with Certificate Authorities and secure authentication protocols
  17. Certifications such as CISSP, CEH, or CISM are highly desirable
  18. Experience designing and maintaining ETL pipelines using tools like Spark, NiFi, and Pentaho
  19. Proficiency in data modeling, governance, and cataloging across structured and unstructured datasets
  20. Hands-on experience with Elasticsearch, Neo4j, and other graph or search databases
  21. Ability to transform and enrich data for analytics using Python, SQL, and cloud-native tools
  22. Experience developing and deploying machine learning models using TensorFlow, PyTorch, or SageMaker
  23. Familiarity with unsupervised learning techniques and feature engineering for large-scale datasets
  24. Ability to integrate ML workflows into data platforms and cloud environments
  25. Knowledge of retrieval augmented generation (RAG) and modern AI-driven analytics is a plus
  26. Full-stack development experience across desktop, web, and cloud platforms
  27. Proficiency with front-end frameworks like React and back-end tools including REST APIs and containerized services
  28. Experience with Git, JIRA, and CI/CD pipelines for agile software delivery
  29. Familiarity with DevSecOps practices and secure coding standards
  30. Experience managing Microsoft Office 365, Windows environments, and endpoint configuration tools (MECM, GPO)
  31. Ability to troubleshoot performance issues and maintain compliance with enterprise security policies
  32. Familiarity with Active Directory, DHCP, and SQL Server in enterprise settings
  33. Understanding of sponsor-specific systems and mission environments is highly valued
  34. Strong technical writing skills for SOPs, system documentation, and stakeholder briefings
  35. Experience using Confluence, JIRA, and other collaboration platforms for task tracking and reporting
  36. Ability to translate complex technical concepts for non-technical audiences
  37. Proven success in cross-functional team environments and stakeholder engagement
  38. Experience with Docker, Kubernetes, and container orchestration in cloud environments
  39. Familiarity with data visualization tools such as Tableau and BI platforms
  40. Hands-on experience with forensic analysis tools and graph database queries