ZipRecruiter

Log In

1

Ai Rag Jobs in Washington, DC (NOW HIRING)

Tekcel8

Gen AI

Washington, DC · On-site

The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, vector databases, and cloud-native AI ...

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 ...

Steampunk

Senior AI Developer

Mclean, VA · Hybrid

$55 - $72.75/hr

We are seeking a dynamic, forward-thinking Senior AI Software Engineer (GenAI, Agents & RAG) to assist in the design and implementation of enterprise-wide AI-powered tools, workflows, and practices ...

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

Steampunk

Senior AI Developer

Mclean, VA · On-site

$55 - $72.75/hr

Overview We are seeking a dynamic, forward-thinking Senior AI Software Engineer (GenAI, Agents & RAG) to assist in the design and implementation of enterprise-wide AI-powered tools, workflows, and ...

Steampunk

Senior AI Developer

Mclean, VA · Hybrid

$55 - $72.75/hr

Overview We are seeking a dynamic, forward-thinking Senior AI Software Engineer (GenAI, Agents & RAG) to assist in the design and implementation of enterprise-wide AI-powered tools, workflows, and ...

previous page

Showing results 41-60

All JobsAi Rag JobsAi Rag Jobs in Washington, DC

Ai Rag information

See Washington, DC salary details

$36.2K

$66K

$94.6K

How much do ai rag jobs pay per year?

As of Aug 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 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 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 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 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 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

Gen AI

Tekcel8

Washington, DC • On-site

Other

Posted 20 days ago

Job description

Title: Gen AI
Location: Washington, DC
Duration: Long-Term Contract
Experience: 8–15 Years
Employment Type: Contract

 

Job Summary:

Coforge is seeking an experienced in Generative AI with 8+ years of software engineering experience and strong expertise in designing, developing, and deploying enterprise-grade GenAI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, vector databases, and cloud-native AI services. The role involves building scalable AI applications, integrating LLMs into enterprise systems, and collaborating with cross-functional teams to deliver innovative AI-powered solutions across multiple industries.

Required Skills:

·         8+ years of Software Development experience

·         2+ years of hands-on experience with Generative AI technologies

·         Strong proficiency in Python

·         Experience with Large Language Models (LLMs) including GPT, Claude, Gemini, Llama, or Mistral

·         Hands-on experience with LangChain, LangGraph, LlamaIndex, or Semantic Kernel

·         Experience building RAG (Retrieval-Augmented Generation) solutions

·         Strong knowledge of Prompt Engineering and prompt optimization

·         Experience developing AI Agents and multi-agent workflows

·         Experience with Vector Databases such as Pinecone, ChromaDB, FAISS, Weaviate, or Milvus

·         Experience integrating AI models through REST APIs

·         Strong understanding of embeddings, tokenization, and semantic search

·         Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or OpenAI APIs

·         Experience with Docker and Kubernetes

·         Familiarity with CI/CD pipelines using Azure DevOps, GitHub Actions, or Jenkins

·         Experience with Git, GitHub, or Bitbucket

·         Experience working in Agile/Scrum environments

·         Strong analytical and problem-solving skills

Preferred Skills

·         Azure AI Foundry / Azure AI Studio

·         AWS Bedrock

·         Google Vertex AI

·         Hugging Face Transformers

·         TensorFlow or PyTorch

·         Knowledge Graphs

·         Neo4j

·         Redis

·         Kafka

·         MLflow

·         Databricks

·         FastAPI

·         Streamlit or Gradio

·         MCP (Model Context Protocol)

·         A2A (Agent-to-Agent)

·         AI Observability tools

·         Prompt Flow

·         AI Security and Responsible AI

·         Experience in Banking, Healthcare, Insurance, Retail, or Manufacturing domains

Responsibilities:

·         Design, develop, and deploy enterprise-grade Generative AI applications.

·         Build intelligent AI assistants, copilots, chatbots, and automation solutions.

·         Develop scalable RAG pipelines using vector databases and enterprise data sources.

·         Build AI Agents and orchestrate multi-agent workflows.

·         Integrate LLMs with enterprise applications and APIs.

·         Optimize prompts, retrieval pipelines, and model performance.

·         Develop secure, scalable, and production-ready AI solutions.

·         Collaborate with Product Owners, Architects, Data Scientists, and Engineering teams.

·         Implement monitoring, logging, evaluation, and governance for AI applications.

·         Participate in architecture discussions, code reviews, and technical design sessions.

·         Troubleshoot production issues and continuously improve AI solution performance.

·         Follow software engineering best practices, DevOps processes, and Agile methodologies.

Qualifications

·         Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

·         8–15 years of software engineering experience.

·         2+ years of hands-on Generative AI development experience.

·         Strong communication and stakeholder management skills.

·         Ability to work independently and within distributed Agile teams. Top of Form

Bottom of Form

Apply