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Ai Rag Jobs in Baltimore, MD (NOW HIRING)

Tek Inspirations LLC

Senior AI Engineer

Laurel, MD · On-site

$56.50 - $73/hr

LLMs, Generative AI & RAG * Experience leveraging Gemini, Azure OpenAI, and other Large Language Models. * Strong hands-on experience implementing Retrieval-Augmented Generation (RAG) solutions.

Bigbear.ai

Senior AI Engineer

Annapolis Junction, MD · On-site

$114K - $228K/yr

Overview BigBear.ai is seeking a BigBear.ai is seeking a motivated Senior AI Engineer with a proven ... Design and implement database solutions to support RAG architectures, artifact storage, audit ...

Bigbear.ai

Senior AI Engineer

Annapolis Junction, MD · On-site

$106K - $146K/yr

Overview BigBear.ai is seeking a BigBear.ai is seeking a motivated Senior AI Engineer with a proven ... Design and implement database solutions to support RAG architectures, artifact storage, audit ...

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All JobsAi Rag JobsAi Rag Jobs in Baltimore, MD

Ai Rag information

See Baltimore, MD salary details

$31.8K

$57.9K

$83K

How much do ai rag jobs pay per year?

As of Aug 6, 2026, the average yearly pay for ai rag in Baltimore, MD is $57,875.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,700.00 and $64,600.00 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 Baltimore, MD? For Ai Rag jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Baltimore, MD look for? The top searched job categories for Ai Rag jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Ai Rag jobs? Cities near Baltimore, MD with the most Ai Rag job openings:
Ai Rag jobs near you

Senior AI Engineer

Tek Inspirations LLC

Laurel, MD • On-site

$56.50 - $73/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Experience Required

  • 8+ years preferred (manager emphasized a very senior resource).
  • Must possess senior-level engineering maturity.
  • Candidate may currently be a Senior AI Engineer, Senior Software Engineer, or Working Tech Lead.
  • Looking for someone capable of operating as a Tech Lead while remaining hands-on with coding. 
    Must have: 
  1. Google Cloud Platform (Google Cloud Platform) Experience
    1. Hands-on experience building and deploying solutions in Google Cloud Platform.
    2. Azure experience is acceptable in addition to Google Cloud Platform
  2. LLMs, Generative AI & RAG
    1. Experience leveraging Gemini, Azure OpenAI, and other Large Language Models.
    2. Strong hands-on experience implementing Retrieval-Augmented Generation (RAG) solutions. 
  3. Agent Framework Experience
    1. Direct experience with Google ADK, LangGraph, or similar agentic AI frameworks.
    2. Building AI agents/bots
  4. Senior-Level, Hands-On Engineer
    1. 6+ years of experience (preferably 8+).
  • Must be a "working tech lead" type of engineer who owns code and actively develops rather than just leading projects. 
    Top Must-Haves:
    •  Design and develop AI applications and intelligent agents on Google Cloud Platform.
    • Develop AI-powered bots and automation solutions.
    • Implement and maintain RAG (Retrieval Augmented Generation) solutions.
    • Leverage Gemini, Azure OpenAI, and other large language models.
    • Build solutions using agent frameworks such as Google ADK and LangGraph.
    • Perform hands-on coding and development activities.
    • Collaborate with technical leads and architects to deliver AI initiatives.
    • Participate in code ownership, architecture discussions, and solution design.
    • Grow into a technical leadership role while remaining highly hands-on

Must Have

  • Google Cloud Platform (Google Cloud Platform) experience.
  • AI/ML engineering experience.
  • Google ADK framework experience.
  • LangGraph experience.
  • Experience leveraging LLMs.
  • Gemini experience.
  • Azure OpenAI experience.
  • RAG implementation experience.
  • Python development.
  • React or Next.js.
  • TypeScript.
  • Strong software engineering background.
  • Hands-on development experience building AI products. 
     

Nice to Have

  • Experience leading development teams.
  • Agentic AI development experience.
  • Prior experience serving as a Tech Lead.
  • Experience architecting enterprise AI solutions.
  • Multi-cloud experience with Azure alongside Google Cloud Platform
     

What Will Make Someone Successful?

  • Extensive hands-on AI development experience.
  • Strong Google Cloud Platform expertise.
  • Deep knowledge of LLMs, Gemini, Azure OpenAI, and RAG.
  • Ability to own code and development efforts independently.
  • Comfortable leading technical direction while still contributing code.
  • Strong communication and collaboration skills.
  • Ability to work effectively within the Covista PMO environment. 
     

Previous Companies / Background Targets

Target candidates from organizations actively building:

  • Enterprise AI applications.
  • Conversational AI solutions.
  • Agentic AI platforms.
  • Cloud-native AI products on Google Cloud Platform or Azure.
  • LLM-based enterprise solutions. (Suggested based on stated technical requirements.) 

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