This role blends frontend and backend engineering with Generative AI, RAG pipelines, ML model development, MLOps, and enterprisescale cloud deployment. You will collaborate with architects, software ...
This role blends frontend and backend engineering with Generative AI, RAG pipelines, ML model development, MLOps, and enterprisescale cloud deployment. You will collaborate with architects, software ...
The Generative AI Applications Engineer will be responsible for developing secure and scalable GenAI applications, focusing on agentic workflows and RAG systems for various federal missions.
The Generative AI Applications Engineer will be responsible for developing secure and scalable GenAI applications, focusing on agentic workflows and RAG systems for various federal missions.
The Generative AI Applications Engineer will be responsible for developing secure and scalable GenAI applications, focusing on agentic workflows and RAG systems for various federal missions.
The Generative AI Applications Engineer will be responsible for developing secure and scalable GenAI applications, focusing on agentic workflows and RAG systems for various federal missions.
The Generative AI Applications Engineer will be responsible for developing secure and scalable GenAI applications, focusing on agentic workflows and RAG systems for various federal missions.
The Generative AI Applications Engineer will be responsible for developing secure and scalable GenAI applications, focusing on agentic workflows and RAG systems for various federal missions.
Strong understanding of LLMs, generative AI, RAG architectures, AI agent frameworks, and Microsoft 365 Copilot.Proven experience driving business value through Microsoft 365 Copilot.Expertise in ...
Strong understanding of LLMs, generative AI, RAG architectures, AI agent frameworks, and Microsoft 365 Copilot.Proven experience driving business value through Microsoft 365 Copilot.Expertise in ...
Palantir Foundry RAG App Engineer Location: Rosslyn, VA (hybrid) Blue Rose Consulting Group, Inc ... Experience deploying AI-enabled applications into production or mission operational environments
New
Palantir Foundry RAG App Engineer Location: Rosslyn, VA (hybrid) Blue Rose Consulting Group, Inc ... Experience deploying AI-enabled applications into production or mission operational environments
New
We're seeking a versatile Senior/Lead AI Engineer to architect and build secure, scalable AI solutions across the full stack. You'll work on LLM integration, RAG pipelines, backend services, frontend ...
We're seeking a versatile Senior/Lead AI Engineer to architect and build secure, scalable AI solutions across the full stack. You'll work on LLM integration, RAG pipelines, backend services, frontend ...
Palantir Foundry RAG App Engineer Location: Rosslyn, VA (hybrid) Blue Rose Consulting Group, Inc ... through AI-enabled workflows, ontology-driven modeling, and scalable Foundry application ...
New
Palantir Foundry RAG App Engineer Location: Rosslyn, VA (hybrid) Blue Rose Consulting Group, Inc ... through AI-enabled workflows, ontology-driven modeling, and scalable Foundry application ...
New
AI Engineer
Richmond, VA · On-site +1
$52.88/hr
Develop and deploy LLM based Agentic AI and automation solutions using RAG or finetuning foundation models. Develop and deploy LLM based Agentic AI and automation solutions using RAG or finetuning ...
AI Engineer
Richmond, VA · On-site +1
$52.88/hr
Develop and deploy LLM based Agentic AI and automation solutions using RAG or finetuning foundation models. Develop and deploy LLM based Agentic AI and automation solutions using RAG or finetuning ...
AI Architect/ AI Engineer
$64.75 - $85.25/hr
... RAG, vector databases, and cloud deployments. · Practical experience with GitHub Copilot adoption patterns including guardrails, prompt library management, extensions, and metrics · Salesforce ...
AI Architect/ AI Engineer
$64.75 - $85.25/hr
... RAG, vector databases, and cloud deployments. · Practical experience with GitHub Copilot adoption patterns including guardrails, prompt library management, extensions, and metrics · Salesforce ...
AI/ML Engineer
Reston, VA · On-site
AI/ML Engineer (Python, AWS, GenAI) Location: Reston, VA (In-person interviews required) Candidate ... Architect and operationalize RAG pipelines , embeddings, vector databases, and LLM-powered ...
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AI/ML Engineer
Reston, VA · On-site
AI/ML Engineer (Python, AWS, GenAI) Location: Reston, VA (In-person interviews required) Candidate ... Architect and operationalize RAG pipelines , embeddings, vector databases, and LLM-powered ...
Must have experience designing and deploying LLM-based systems, including RAG, tool-calling, and multi-agent patterns, as well as a strong understanding of modern AI architectures such as embeddings ...
Must have experience designing and deploying LLM-based systems, including RAG, tool-calling, and multi-agent patterns, as well as a strong understanding of modern AI architectures such as embeddings ...
Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval ... Implement and maintain RAG pipelines, including document processing, embedding generation ...
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Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval ... Implement and maintain RAG pipelines, including document processing, embedding generation ...
AI Developer
Mclean, VA · On-site
$140K - $190K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
AI Developer
Mclean, VA · On-site
$140K - $190K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
AI Developer
$140K - $190K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
AI Developer
$140K - $190K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
AI Developer
$140K - $190K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
AI Developer
$140K - $190K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
AI Engineer
Reston, VA · On-site
$90K - $190K/yr
Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...
AI Engineer
Reston, VA · On-site
$90K - $190K/yr
Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...
AI Developer
Mclean, VA · On-site
$140K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
AI Developer
Mclean, VA · On-site
$140K/yr
Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...
RAG pipelines * Vector databases * Knowledge graph integrations * Design and implement AI governance frameworks including: * Responsible AI * AI Guardrails * Model monitoring * Risk management
New
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RAG pipelines * Vector databases * Knowledge graph integrations * Design and implement AI governance frameworks including: * Responsible AI * AI Guardrails * Model monitoring * Risk management
New
Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...
Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...
Ai Rag information
What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?
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 some common challenges faced by AI RAG (Retrieval-Augmented Generation) 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 AI RAGs?
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 is the difference between Ai Rag vs Data Analyst?
| Aspect | Ai Rag | Data Analyst |
|---|---|---|
| Required Credentials | Typically a diploma or certification in AI, machine learning, or related fields | Bachelor's degree in statistics, mathematics, or related fields |
| Work Environment | Tech companies, AI startups, research labs | Business, finance, healthcare, and various industries |
| Employer & Industry Usage | Primarily in AI development and research | Across industries for data interpretation and decision-making |
| Common Search & Comparison | Yes | Yes |
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 Virginia? For Ai Rag jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Virginia look for? The top searched job categories for Ai Rag jobs in Virginia are:
What cities in Virginia are hiring for Ai Rag jobs? Cities in Virginia with the most Ai Rag job openings:
Job description
Job Summary
Client is seeking a highly skilled AI/ML Full Stack Developer to design, develop, and deploy modern fullstack applications enhanced with advanced Artificial Intelligence capabilities. This role blends frontend and backend engineering with Generative AI, RAG pipelines, ML model development, MLOps, and enterprisescale cloud deployment. You will collaborate with architects, software engineers, data engineers, and business stakeholders to translate requirements into productiongrade AI-powered software solutions. The ideal candidate brings strong software engineering fundamentals combined with handson experience developing and operationalizing AI/ML systems on Microsoft Azure.
Major Responsibilities
Full Stack Application Development
Develop and maintain modern web applications using React, React Native, HTML, CSS, JavaScript/TypeScript
Build backend services and REST/GraphQL APIs using Node.js and microservices-based patterns
Design, optimize, and execute complex SQL queries across multiple relational and nonrelational database systems
Implement secure, scalable integrations with cloud, data, and AI services.
Participate in code reviews, architecture discussions, and Agile ceremonies.
Utilize Git/GitHub for version control and DevOps workflows
Apply software design patterns and best practices in full-stack development.
Generative AI & Retrieval-Augmented Generation (LLM Applications)
Build LLM powered applications for text generation, summarization, Q&A, conversational AI, and enterprise knowledge search.
Develop RAG pipelines using embeddings, vector databases, knowledge bases, and grounding techniques with enterprise data.
Implement Azure OpenAI, Cognitive Search, and related services to build secure, compliant GenAI solutions.
Integrate LLMs into backend applications, microservices, and enterprise platforms.
Optimize prompts, system instructions, and orchestration patterns to ensure quality, reliability, and cost efficiency.
AI Agents & Agentic Automation
Design and implement single agent and multi agent systems for intelligent automation and decisioning.
Build autonomous and semi-autonomous agents that perceive, plan, act, and interact with tools, APIs, and event-driven systems.
Develop agentic workflows for complex enterprise processes using Azure and modern orchestration frameworks.
ML Model Based AI (Classical ML & Deep Learning)
Design, develop, and deploy classical ML and deep learning models using platforms such as Azure Machine Learning, PyTorch, and Scikit Learn.
Perform data preprocessing, feature engineering, model training, hyperparameter tuning, validation, and performance optimization.
Ensure resilience, scalability, and lifecycle management for all production models.
Work with large-scale datasets, performing data preprocessing, feature engineering, and model validation.
Deploy AI models using cloud-based platforms such as Azure AI/ML,.
Ensure AI/ML solutions align with enterprise security, compliance, and governance standards.
Education and Experience Requirements:
Requires bachelor's degree (or international equivalent) and 7 + years of relevant experience or 11+ years of relevant work experience without degree
3-5 years of experience in AI/ML development, including designing and deploying ML models.
3-5 years in Full Stack Development Experience
Knowledge, understanding and practical experience of web & mobile development technologies such as HTML, CSS, React & React Native, JavaScript/TypeScript.
Good understanding of latest front-end frameworks and backend technologies
Practical knowledge and work experience with NodeJS, Reactjs, React-Native and GraphQL.
Good knowledge and understanding of RESTful API principles.
Good understanding of relational databases and querying using SQL.
Strong software engineering background (Python, REST APIs, microservices, event-driven systems).
Hands-on experience with Azure Machine Learning, Azure OpenAI, Cognitive Services, and Azure Data Lake.
Experience building RAG systems, vector embeddings, and knowledge retrieval pipelines.
Proficiency in big data processing technologies such as Databricks, Azure Data Factory, or Kafka.
Experience with multi-agent systems or agentic AI orchestration frameworks.
Background in NLP, computer vision, or advanced deep learning architectures.
Experience with vector databases (Azure AI Search vector store).
Expertise in AI/ML frameworks like PyTorch, Keras, or Scikit-learn.
Experience with NLP, Computer Vision, Deep Learning, and Generative AI models.
Strong knowledge of MLOps, CI/CD for AI model deployment, and containerization (Docker, Kubernetes).
Familiarity with data engineering, ETL pipelines, and SQL/NoSQL databases.
Experience working in an enterprise environment with large-scale AI deployments.
Strong analytical, problem-solving, and communication skills.
Preferred Skills:
Experience with the Microsoft Agent Framework, Azure AI Foundry and Agent Service, Microsoft 365 Agents SDK/Toolkit, Semantic Kernel (including AutoGen convergence), RAG and vector based retrieval pipelines for agents, and enterprise grade agent tooling and integrations. based retrieval pipelines for agents, and enterprise grade agent tooling and integrations.
Experience in Multiagent orchestration patterns, Advanced retrieval for agents: GraphRAG, structured data tools (NL2SQL), and domain specific agents. agent orchestration patterns specific agents
About Smart Synergies
Sourced by ZipRecruiter
Industry
Recruiting and staffing services
Company size
1 - 10 Employees
Headquarters location
Ashburn, VA, US
Year founded
2010