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Ai Rag Jobs in Washington, DC (NOW HIRING)

YCG

Be Seen First

Senior Data Engineer

Washington, DC · Remote

$120K - $175K/yr

AI RAG Pipeline Data Ingestion & Security: Collaborate with the AI Engineer to feed unstructured programmatic files into Azure Blob Storage and structure them for Azure AI Search vectorization.

New

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Closure Technologies is seeking an AI/ML Engineer who will implement and maintain Retrieval ... Responsibilities : • Implement and maintain RAG pipelines, including document processing ...

Que Technology Group

AI Engineer

Fort George G Meade, MD · On-site

$120 - $160/hr

Que Technology Group, Inc., is looking for a motivated AI Engineer with a proven track record in ... Design and implement database solutions to support RAG architectures, artifact storage, audit ...

Apex Systems

AI Quality Engineer

Merrifield, VA · On-site

$68.88 - $90.92/hr

Validate Retrieval-Augmented Generation (RAG) solutions built using Azure AI Search, Azure AI Foundry, LangChain, and LangGraph.* Perform architecture reviews and quality assessments for AI solutions ...

Merican

AWS AI Engineer

Herndon, VA · On-site

Design and optimize Retrieval-Augmented Generation (RAG) pipelines for performance and scalability * Implement AI governance frameworks, including security guardrails and cost optimization strategies

S27a

AI/ML Engineer Onsite (Washington, DC)

Washington, DC · On-site

$130 - $170/hr

RAG * AWS Job Summary Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you'll ...

New

ARSIEM

361 - AI Engineer

Linthicum, MD · On-site

$126 - $141/hr

AI Engineer ARSIEM is looking for a motivated AI Engineer with a proven track record in software ... Design and implement database solutions to support RAG architectures, artifact storage, audit ...

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Ai Rag information

See Washington, DC salary details

$36.2K

$66K

$94.6K

How much do ai rag jobs pay per year?

As of Sep 7, 2026, the average yearly pay for ai rag in Washington, DC is $65,968.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,500.00 and $73,600.00 per year, depending on experience, location, and employer.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What are popular job titles related to Ai Rag jobs in Washington, DC?

For Ai Rag jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Ai Rag jobs in Washington, DC look for?

The top searched job categories for Ai Rag jobs in Washington, DC are:

Ai Rag jobs near you

Senior Data Engineer

YCG

Washington, DC • Remote

$120K - $175K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

New

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Job description

The Senior Data Engineer will own the end-to-end data pipelines that ingest historical and transactional records from rigid legacy Systems of Record (SOR) and structure them into a high-performance environment on Databricks. The ideal candidate will be responsible for resolving legacy synchronization gaps, eradicating administrative tracking burdens, and establishing an auditable, compliant, and performant data foundation to feed downstream Power Platform applications and Azure AI Search-powered Retrieval-Augmented Generation (RAG) models.


Core Technical Responsibilities

  • Databricks Spark Pipelines & ETL Engineering: Build and scale distributed PySpark and Spark SQL pipelines on Azure Databricks to ingest raw scheduled feeds (nightly/weekly flat files or database links) from source systems. Ensure high-performance data cleaning and schema enforcement.
  • Medallion Lakehouse Architecture Implementation: Develop and maintain Delta Lake schemas across the Medallion Architecture. Maintain exact, append-only copies in the Bronze layer; build automated multi-source joins and reconciliation mapping in the Silver layer and publish optimized multi-dimensional tables in the Gold layer representing unified, historical actuals.
  • Continuous Reconciliation Engine & SQL Triggers: Design and deploy Databricks automated jobs that scan the Silver layer to proactively identify and flag unmatched, misaligned, or trailing ledger transactions prior to monthly/quarterly closeouts. Write scheduled SQL trigger procedures to manage and clear 'Pending Internal Holds' inside the Azure SQL serving layer as soon as transaction matches appear in core warehouse feeds.
  • Database Serving Layer Optimization & Schema Resilience: Manage the Azure SQL Serving Layer to host application metadata, scenario models, routing matrices, and transaction logs. Formulate and enforce multi-tenant partitioning strategies using mandatory Fiscal_Year and Record_Version schema columns. Drive the data ingestion granularity strategy, keeping detailed transactions in Delta Lake while rolling up aggregated monthly balances in Azure SQL to ensure sub-second query times inside Dataverse Virtual Tables and Power Apps.
  • Downstream Integration & Virtual Table Provisioning: Configure and optimize SQL views exposed as Dataverse Virtual Tables, enabling the Power Platform front-end (Model-Driven power user dashboards and embedded Canvas apps) to read real-time blended actuals without data replication or excessive storage fees. Standardize environment variables inside the deployment profile framework to prevent unmanaged, hardcoded environmental settings.
  • AI RAG Pipeline Data Ingestion & Security: Collaborate with the AI Engineer to feed unstructured programmatic files into Azure Blob Storage and structure them for Azure AI Search vectorization. Ensure all data structures adhere to strict Federal compliance, maintaining data boundaries within the secure FAA Azure GovCloud (GCC) tenant and conforming to FedRAMP, FISMA, and Section 508 accessibility standards.

Required Experience & Technical Skill Set

  • Databricks Mastery: Minimum of 4-6 years of direct experience with Azure Databricks, Delta Lake, and Unity Catalog within a production cloud ecosystem.
  • Apache Spark & Coding: Advanced proficiency in PySpark and Spark SQL for developing distributed, high-throughput ETL/ELT pipelines and handling high-concurrency relational data.
  • Relational Database Expertise: Strong knowledge of Azure SQL Database / Microsoft SQL Server, including schema partitioning, performance tuning, indexed views, and complex triggers/stored procedures.
  • Integration & Pipeline Patterns: Experience with automated ingestion pipelines utilizing flat files, API connectors, serverless Azure Functions, and Power Automate flow integrations.
  • Power Platform Alignment: Understanding of Microsoft Dataverse Virtual Tables and Environment Variables to manage connection references and abstract code across Dev, Test, UAT, and Prod environments.
  • Federal Compliance & Security: Direct experience operating within Azure GovCloud (GCC), ensuring strict compliance with FedRAMP (Moderate/High controls), FISMA ATO standards, and NIST SP 800-218 supply chain requirements.
  • Federal Financial Systems (Preferred): Highly preferred experience working with federal financial systems of record such as Oracle Delphi (SGL accounting strings), PRISM, and/or federal payroll structures (REGIS/FPPS).

Company Description

About YCG

YCG is a fast-growing, remote-first technology company focused on delivering innovative solutions across the Microsoft ecosystem. We specialize in Power Platform, Dynamics 365, and Azure, helping organizations modernize operations, automate workflows, and unlock data-driven insights.

Our expertise includes Power Apps, Power BI, Power Pages, and Dataverse, combined with advanced capabilities in Azure AI/ML, cloud compute, analytics, Purview, eDiscovery, and integration services. We build scalable, intelligent solutions that drive efficiency and support smarter decision-making.

We bring experience working in government contracting environments, including familiarity with agencies such as the FAA, as well as delivering solutions across finance, contracts, and program management domains. We understand the importance of security, compliance, and performance in highly regulated industries.

As a growing team, we offer a collaborative culture, flexible remote work, and opportunities to work on cutting-edge cloud and AI solutions. If you're looking to make an impact and grow with a company on the rise, we’d love to connect.