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Entry Level Retrieval Augmented Generation Jobs in Virginia

Tata Consultancy Service Limited

Engineer

Mclean, VA · On-site

$100K - $120K/yr

... Retrieval-Augmented Generation (RAG) using vector databases (Pinecone, FAISS, Chroma DB, Azure AI Search) to enable enterprise-grade QA and summarization systems. • Integrate GenAI models into ...

CYNET SYSTEMS

Senior Agentic AI Engineer

Reston, VA · On-site

$59 - $77/hr

Retrieval-Augmented Generation (RAG). * Microsoft Azure. * Azure AI Search. * React. * TypeScript. * Node.js. * Microsoft Agent Framework. * Azure AI Foundry. * OpenTelemetry. * Docker. * Kubernetes.

Hsp-Direct,-LLC-

AI Solution Developer

Ashburn, VA · On-site

$125 - $150/hr

Retrieval augmented generation * Authentication and access control * Source control, CI/CD, and automated testing * Migrating data and applications from an old system to a new one Plus: * SQL Server

HSP Direct

AI Solution Developer

Ashburn, VA · On-site

Retrieval augmented generation * Authentication and access control * Source control, CI/CD, and automated testing * Migrating data and applications from an old system to a new one Plus: * SQL Server

Twenty Technologies, Inc

Applied AI Engineer

Arlington, VA · On-site

$159K - $263K/yr

Build retrieval-augmented generation (RAG) systems that ground model outputs in external knowledge. * Develop and optimize model serving infrastructure for production deployments. * Design evaluation ...

Holland & Knight

AI Legal Engineer

Richmond, VA · On-site

Demonstrated ability to design and build AI-enabled workflows in legal or professional-services settings, including prompt engineering, retrieval-augmented generation (RAG) concepts, and evaluation ...

HSP Direct

Business Solutions Developer

Ashburn, VA · On-site

Retrieval augmented generation * Authentication and access control * Source control, CI/CD, and automated testing * Migrating data and applications from an old system to a new one Plus: * SQL Server

HSP Direct LLC

Business Solutions Developer

Ashburn, VA · On-site

$125 - $150/hr

Retrieval augmented generation * Authentication and access control * Source control, CI/CD, and automated testing * Migrating data and applications from an old system to a new one Plus: * SQL Server

HSP Direct

Business Solutions Developer

Ashburn, VA · On-site

Retrieval augmented generation * Authentication and access control * Source control, CI/CD, and automated testing * Migrating data and applications from an old system to a new one Plus: * SQL Server

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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 September 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution.

AI Implementation Engineer - JobID-0245

Arlington, VA • On-site

Innovative Defense Technologies (IDT)
IT Services • 51 - 200 employees
Learn more about Innovative Defense Technologies (IDT)external

$114K - $231K/yr

Other

Re-posted 22 hours ago

Job description

About The Role:
Innovative Defense Technologies (IDT), a leading defense technology company, is seeking an AI Implementation Engineer to be part of our Warfare Systems team and based out of our Arlington, VA or Mount Laurel, NJ location.
The AI Implementation Engineer will design and deliver engineering-focused AI solutions that move beyond demos into reliable, mission-relevant systems. This role is ideal for an engineer who has extensive experience with commercially available AI tooling/chat, hosting LLM servers and has demonstrated ability to build end-to-end capabilities including MCP integrations, RAG pipelines, tool-using agents, and production-grade AI workflows.
Clearance & Location Requirements:
  • All applicants must be able to obtain/maintain an active Secret U.S. Security Clearance.
  • This is an on-site position. Requiring at least 3 days in office, based out of our Arlington, VA location or Mt. Laurel, NJ location.
Department Engineering Employment Type Full Time Location Arlington, VA Address 4401 Wilson Boulevard Suite 810, Arlington, Virginia, 22203 Open in Google Maps Workplace type Hybrid Compensation $114,000 - $231,000 / year Key Responsibilities
What You Will Do:
  • Design and Build AI Solutions for On-Prem systems in Air-Gapped environment: Design and implement end-to-end agentic AI systems that support planning, reasoning, tool use, and multi-step execution in real-world environments. Build modular, testable components that move from prototype to operational capability.
  • Integrate Models and Tools for On-Prem systems in Air-Gapped environment: Develop integrations across LLMs, APIs, data sources, and Model Context Protocol (MCP) interfaces to enable intelligent agents to interact with external systems, retrieve context, and take action safely and reliably.
  • Develop Retrieval Pipelines for On-Prem systems in Air-Gapped environment: Build and optimize Retrieval-Augmented Generation (RAG) pipelines that connect models to live knowledge sources, structured data, and enterprise content to improve factual grounding, contextual relevance, and response quality.
  • Engineer Conversational and Agentic Interfaces for On-Prem systems in Air-Gapped environment: Create conversational systems and intelligent agents with memory, contextual awareness, adaptive decision-making, and support for multi-turn user and system interactions.
  • Implement and Evaluate AI Workflows for On-Prem systems in Air-Gapped environment: Translate technical objectives into working pipelines, run experiments, evaluate agent behavior, and iterate on prompts, orchestration logic, retrieval quality, and system performance to improve reliability and usability.
  • Architect local infrastructure to size, config, and optimize local CPU/GPU workloads, utilizing quantization techniques to maximize throughput, etc.
  • Orchestrate disconnected environments, design and maintain offline model update pipelines, local package mirrors, etc.
  • Scope and Define Requirements: Gather, document, and validate technical and functional requirements from project artifacts, stakeholders, and mission needs to ensure feasibility, completeness, and alignment with operational goals.
  • Collaborate Across Teams: Work closely with engineers, technical leads, and mission stakeholders to integrate AI capabilities into broader software and system architectures. Participate in technical reviews, design discussions, and delivery planning.
  • Support Technical Quality: Contribute to testing, debugging, and performance optimization of AI-enabled applications, including edge cases involving context management, retrieval failures, tool execution, and orchestration logic.
  • Learn and Apply Emerging Practices: Stay current on advances in LLMs, agent frameworks, orchestration methods, and applied AI engineering practices, and bring that knowledge into practical system design and implementation.
  • Communicate Technical Work: Clearly document architectures, workflows, assumptions, and implementation decisions so that solutions are maintainable, explainable, and transferable across teams.

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