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Entry Level Retrieval Augmented Generation Jobs in Virginia

Steampunk

AI Evaluation Scientist

Mclean, VA

$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.

IBM Computing

Full-Stack Data Engineer (TS/SCI)

Hampton, VA · On-site

$120 - $150/hr

Experience in advanced AI techniques - fine-tuning ML models and LLMs, implementing chat sessions via API, retrieval-augmented generation, agentic workflows/tooling/function calling, and/or context ...

New

IBM Computing

Full-Stack Data Engineer (TS/SCI)

Herndon, VA · On-site

$90 - $120/hr

Experience in advanced AI techniques - fine-tuning ML models and LLMs, implementing chat sessions via API, retrieval-augmented generation, agentic workflows/tooling/function calling, and/or context ...

New

IBM Computing

Full-Stack Data Engineer (TS/SCI)

Ashburn, VA · On-site

$90 - $130/hr

Experience in advanced AI techniques - fine-tuning ML models and LLMs, implementing chat sessions via API, retrieval-augmented generation, agentic workflows/tooling/function calling, and/or context ...

New

Steampunk

AI Evaluation Scientist

Mclean, VA

$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.

Steampunk

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.

Steampunk

AI Evaluation Scientist

Mclean, VA

$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.

Steampunk

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.

Steampunk

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.

Steampunk

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.

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All JobsRetrieval Augmented Generation JobsEntry Level Retrieval Augmented Generation JobsEntry Level Retrieval Augmented Generation Jobs in Virginia

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 are popular job titles related to Entry Level Retrieval Augmented Generation jobs in Virginia?

For Entry Level Retrieval Augmented Generation jobs in Virginia, the most frequently searched job titles 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:

Entry Level Retrieval Augmented Generation jobs near you
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.

AI Evaluation Scientist

Steampunk

Mclean, VA

$105K - $145K/yr

Full-time

Re-posted 5 days ago

Job description

We are looking for an AI Evaluation Scientist to design and execute evaluation processes that ensure our predictive and generative AI systems are accurate, reliable, safe, and aligned with mission requirements. This role is essential for establishing trust in AI solutions and supporting continuous improvement across the AI lifecycle. The AI Evaluation Scientist will work closely with engineers, data scientists, governance analysts, and product teams to develop evaluation metrics, build test harnesses, analyze model behavior, and support responsible deployment. 


  • Implement evaluation frameworks for AI models, including accuracy, robustness, relevance, bias, hallucination rate, and safety metrics.
  • Build and maintain automated evaluation scripts, tests, and pipelines that assess AI model outputs and detect performance drift over time.
  • Develop benchmark datasets, challenge sets, and scenario-based test cases tailored to mission and user needs.
  • Perform structured error analysis and behavioral audits of LLMs, retrieval-augmented generation (RAG) systems, and predictive models, documenting findings and improvement recommendations.
  • Collaborate with AI Developers, LLMOps Engineers, and Data Scientists to support iterative experimentation, model hardening, and quality improvements.
  • Contribute to the design of human-in-the-loop evaluation workflows, integrating qualitative and quantitative insight into evaluation reports.
  • Assist in mapping evaluation outcomes to responsible AI principles such as fairness, transparency, reliability, and safety.
  • Partner with AI Governance Analysts to ensure evaluation outputs support compliance, documentation, and risk assessments.
  • Stay current with emerging evaluation tools, frameworks, metrics, and research related to LLM assessment and generative AI reliability.
  • Document evaluation processes, criteria, and results for both technical and non-technical audiences.
  • You will contribute to the growth of our AI & Data Exploitation Practice! 

  • Ability to hold a position of public trust with the U.S. government.
  • Bachelor’s or Master’s degree in Computer Science, Statistics, Machine Learning, Cognitive Science, Human-Computer Interaction, Data Science, or a related field.
  • 2+ years of experience evaluating machine learning models, NLP systems, or generative AI models (LLMs preferred).
  • Familiarity with evaluation metrics, statistical testing, dataset creation, and experimental design for AI systems.
  • Proficiency in Python and relevant libraries such as PyTorch, Hugging Face, scikit-learn, LangChain.
  • Proficiency in AI evaluation frameworks such as Ragas.
  • Experience analyzing structured and unstructured data, including text, documents, and embeddings.
  • Understanding of LLM behavior, prompt evaluation, retrieval pipelines, or RAG architectures.
  • Exposure to responsible AI concepts and governance-aligned evaluation criteria (e.g., fairness, transparency, reliability).
  • Strong analytical skills with the ability to interpret model weaknesses, extract insights, and recommend actionable improvements.
  • Excellent written and verbal communication skills, with the ability to present evaluation findings clearly to technical and non-technical stakeholders.
  • Experience working in agile or iterative development environments is a plus.
  • Familiarity with OWASP LLM Top 10 Risks. 
  • NIH experience. 
  • Relevant certifications (helpful but not required): 
    • NIST AI RMF (AISIC)
    • INFORMS CAP
    • AWS/Azure/Google ML Certifications. 
  • Local to Washington, DC metro area preferred. 

Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $105,000 to $145,000.  The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk’s total compensation package for employees. Learn more about additional Steampunk benefits here. 

Identity Statement

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors.  Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges.  As an employee owned company, we focus on investing in our employees to enable them to do the greatest work of their careers – and rewarding them for outstanding contributions to our growth. If you want to learn more about our story, visit http://www.steampunk.com.

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