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Remote Rag Jobs in Washington (NOW HIRING)

This role is remote with a preference for candidates located in Virginia, Maryland, or Washington ... Integrate AI/ML capabilities (Vertex AI, Gemini APIs, embeddings, RAG) into enterprise Java and ...

Experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) solutions ... Working Environment : eSimplicity supports a remote work environment operating within the Eastern ...

Forward Deployed Engineer

Washington, DC · On-site +1

$141K - $236K/yr

Knowledge of RAG, Hybrid RAG, MCP * Experience creating, maintaining, and communicating complex ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

AI/ML Engineer

Washington, DC · On-site +1

$130K - $170K/yr

Implement Retrieval-Augmented Generation (RAG), semantic search, and knowledge retrieval ... Hybrid or Remote with limited travel Benefits: Expression offers competitive salaries and benefits ...

New

Forward Deployed Engineer

Washington, DC · On-site +1

$141K - $236K/yr

Knowledge of RAG, Hybrid RAG, MCP * Experience creating, maintaining, and communicating complex ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

Data Engineer II

Columbia, MD · On-site +1

$93K - $100K/yr

Experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) solutions ... Working Environment : eSimplicity supports a remote work environment operating within the Eastern ...

Solutions Architect

Washington, DC · Remote

$160K - $180K/yr

Now we're building an industry-leading knowledge management and Retrieval-Augmented Generation (RAG ... Remote first organization - 100% Company paid Health/Dental/Vision benefits for you and your ...

... RAG), Multi-Modal AI, and modern AI-enabled web applications. This role is remote/hybrid in the VA/MD/DC area. There may be occasional travel to client site in Washington D.C. Required Clearance:

AI Engineer

Washington, DC · On-site +1

$160K - $180K/yr

... RAG), Multi-Modal AI, and modern AI-enabled web applications. This role is remote/hybrid in the VA/MD/DC area. There may be occasional travel to client site in Washington D.C. Required Clearance:

Solutions Architect

Washington, DC · Remote

$160K - $180K/yr

Now we're building an industry-leading knowledge management and Retrieval-Augmented Generation (RAG ... Benefits for Full Time Employees: - Remote first organization - 100% Company paid Health/Dental ...

ETL Data Engineer

Tysons, VA · Remote

$70 - $88/hr

Description: Hybrid 3 days onsite / 2 days remote in Mclean, VA Our client seeks an ETL Data ... Knowledge of prompt engineering, RAG architectures, and context or memory management. * Experience ...

Strong knowledge of agentic frameworks, orchestration tools, RAG, vector databases, API design, and ... Flexible to work remote with the ability to commute to the corporate office as needed Must have ...

Software Engineer - Product

Washington, DC · On-site +1

$120K - $140K/yr

... Generation (RAG) application. This individual will play a crucial role in building intelligent ... This is a remote position. This position is not eligible for sponsorship or relocation assistance.

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Remote Rag information

What are the key skills and qualifications needed to thrive as a Remote Rag, and why are they important?

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What is a Remote RAG (Retrieval-Augmented Generation) specialist?

A Remote RAG specialist is a professional who works with Retrieval-Augmented Generation (RAG) systems, typically in the field of artificial intelligence and machine learning. RAG combines traditional information retrieval techniques with generative models like large language models to provide more accurate and contextually relevant answers to user queries. Remote RAG specialists often build, fine-tune, and maintain these systems while working from a remote location. They may also work on integrating RAG models into applications, improving retrieval accuracy, and customizing outputs based on user needs.

What are some common challenges faced by professionals working in a remote RAG (Responsible AI Governance) role?

Professionals in remote RAG roles often encounter challenges related to cross-functional collaboration and maintaining clear communication, especially when working across different time zones. Ensuring alignment on ethical AI standards and compliance requirements can be complex, as it typically involves coordinating with data scientists, legal teams, and business stakeholders. Staying current with evolving regulatory frameworks and best practices in AI governance is also essential, demanding continuous learning and adaptability. Building trust and rapport within a remote team can require extra effort, but leveraging digital collaboration tools and regular check-ins can help mitigate these challenges.
What are the most commonly searched types of Rag jobs in Washington? The most popular types of Rag jobs in Washington are:
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AI Engineer (Mid)

AI Engineer (Mid)

Northramp LLC

Washington, DC • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


Job description

We are looking for an Application Architect with strong AI engineering experience to design and build intelligent, agentic applications on Google Cloud Platform. This role sits within an application engineering team and focuses on architecting AI-enabled systems using the Google Agentic Development Kit (ADK), Gemini, and Vertex AI - integrated into enterprise Java/Python backends and cloud-native microservices. You are equally comfortable defining application architecture, designing agentic workflows, writing production-quality code, and translating AI capabilities into practical, mission-aligned solutions for federal stakeholders.

This role is remote with a preference for candidates located in Virginia, Maryland, or Washington DC.

Key Responsibilities
  • Architect and implement AI-enabled application systems on GCP, with a focus on agentic workflows using Google ADK and Gemini Pro.
  • Design human-in-the-loop agentic systems - defining agent roles, tool use, orchestration patterns, and guardrails for responsible, auditable AI behavior.
  • Integrate AI/ML capabilities (Vertex AI, Gemini APIs, embeddings, RAG) into enterprise Java and Python applications via well-designed APIs and microservices.
  • Lead application-layer design decisions: data flow, context management, session handling, and state management within agentic architectures.
  • Collaborate with Data Engineers (BigQuery, Dataform) and Cloud Architects to ensure AI application solutions are grounded in reliable, governed data.
  • Conduct architectural reviews, define coding standards for AI-integrated applications, and mentor engineers on agentic design patterns.
  • Evaluate AI use cases for feasibility, risk, and mission fit; prototype and validate approaches before committing to full builds.
  • Contribute to responsible AI practices: explainability, human oversight, auditability, and alignment with federal AI governance requirements.
  • Stay current on the Google AI ecosystem (Gemini, ADK, Vertex AI Agent Builder) and inform team and leadership on strategic direction.

Requirements

Required Qualifications
  •  5-8 years of software or application engineering experience, with demonstrated focus on AI-integrated or intelligent application design.
  • Hands-on experience with Google ADK or comparable agentic frameworks (LangGraph, LangChain, AutoGen); Google ADK strongly preferred.
  • Proficiency in Python for AI/ML integration; Java experience a plus in application team context.
  • Experience integrating LLM APIs (Gemini, OpenAI, or equivalent) into production application workflows.
  • Solid understanding of agentic design patterns: tool use, multi-agent orchestration, retrieval-augmented generation (RAG), memory and context management.
  • Experience with GCP services: Vertex AI, Cloud Run, GKE, BigQuery, Pub/Sub.
  • Familiarity with REST API design, microservices architecture, and CI/CD pipelines (Harness preferred).
  • Understanding of responsible AI principles: human-in-the-loop design, auditability, bias awareness, and federal AI governance.
Desired Qualifications
  • Experience with Vertex AI Agent Builder, Gemini Code Assist, or Gemini CLI in a development workflow context.
  • Familiarity with GCP-native data tooling: BigQuery, Dataform, Looker.
  • Experience on federal or large-scale enterprise modernization programs.
  • Exposure to FedRAMP/FISMA requirements and security-compliant AI deployment practices.
  • Experience with DevSecOps pipelines (Checkmarx, Invicti, or equivalent SAST/DAST tooling).
Additional Information
  • Successful completion of a client-required background investigation and suitability determination will be required.
  • The ability to obtain and maintain a federal security clearance may be required based on engagement.
  • Bachelor's degree in Computer Science, Software Engineering, or a related field; advanced degree a plus.
  • Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer certification preferred.
  • Security+ desirable.

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Short Term & Long Term Disability
  • Training & Development
  • Work From Home
  • Wellness Resources
  • Employee Bonus Programs