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Generative Ai Testing Jobs in Baltimore, MD (NOW HIRING)

RAKS Group LLC

Gen AI Developer

Woodlawn, MD · On-site

Conduct code reviews, testing, and debugging to ensure application reliability and performance. Stay current with emerging technologies and best practices in Generative AI and full stack development.

Morgan Stanley

VP, AI Compliance Officer

Baltimore, MD

$108K - $185K/yr

What you'll do in the role: > Advise Wealth Management Generative AI and Platforms teams on AI ... Testing teams. > Collaborate with Policy and Training teams to draft, implement, and maintain ...

Dcode Talent LLC

GenAI Engineer

Woodlawn, MD · On-site

Incorporating generative AI models into existing software applications and products. · Research ... control, and testing. · Problem-solving, analytical, and critical thinking skills. · Strong ...

Delviom LLC

Senior GenAI Engineer

Woodlawn, MD · On-site

$108K - $149K/yr

Understanding of fundamental AI and RAG concepts for developing generative AI applications ... Solid experience with software development best practices, including unit testing, continuous ...

Omm IT Solutions

GenAI Engineer

Ellicott City, MD

Incorporating generative AI models into existing software applications and products. \n * Research ... and testing. \n * Problem\-solving, analytical, and critical thinking skills. \n * Strong ...

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Generative Ai Testing information

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$31

$53

$75

How much do generative ai testing jobs pay per hour?

As of Jul 28, 2026, the average hourly pay for generative ai testing in Baltimore, MD is $53.38, according to ZipRecruiter salary data. Most workers in this role earn between $43.94 and $61.15 per hour, depending on experience, location, and employer.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How much do AI testers get paid?

AI testers, involved in evaluating and validating generative AI models, typically earn salaries ranging from $60,000 to $120,000 annually depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in machine learning and data analysis can earn higher wages.

Is AI testing a good career?

AI testing, including roles like Generative AI Testing, is a growing field with increasing demand for skills in machine learning, data analysis, and software quality assurance. It offers opportunities in tech companies, research labs, and startups, often requiring knowledge of AI frameworks and testing tools. The career can be stable and rewarding for those with technical expertise and an interest in AI development.

What are the key skills and qualifications needed to thrive as a Generative AI Testing Specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What is the salary of generative AI tester?

The salary of a generative AI tester typically ranges from $70,000 to $120,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in AI and machine learning can earn higher salaries. Certifications in AI or related fields can also influence compensation.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

How do I become an AI tester?

To become an AI tester, you should have a strong understanding of machine learning concepts, programming skills in languages like Python, and experience with data annotation and model evaluation. Familiarity with AI tools, testing frameworks, and quality assurance processes is also important. Gaining relevant certifications or training in AI and software testing can enhance your qualifications.

What is Generative AI Testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.
What are popular job titles related to Generative Ai Testing jobs in Baltimore, MD? For Generative Ai Testing jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Baltimore, MD look for? The top searched job categories for Generative Ai Testing jobs in Baltimore, MD are:
Generative Ai Testing jobs near you
AI/ML Engineer -- Generative AI Mission Systems

AI/ML Engineer -- Generative AI Mission Systems

Rackner

Laurel, MD • On-site, Remote

Full-time

Posted 5 days ago

Job description

AI/ML Engineer — Generative AI Mission Systems

Remote, U.S.-Based | Periodic onsite collaboration in Laurel, Maryland, approximately every six weeks

Build Applied AI for Secure Mission Software

Help turn generative-AI concepts into dependable capabilities used within secure planning and decision-support software.

At Rackner, you will integrate large language models, retrieval-augmented generation, agentic AI, and inference workflows into an established software application supporting a high-impact national-security mission. You will work across AI, software engineering, cybersecurity, DevSecOps, and customer technical teams to move capabilities beyond standalone demonstrations and into practical product workflows.

This role offers the opportunity to deepen your applied-AI experience, influence how emerging capabilities are designed and evaluated, and contribute to software where reliability, security, and mission usefulness matter.

The position is mainly remote, with team-wide onsite sprint planning in Laurel, Maryland, approximately every six weeks. This position is contingent upon contract award and final customer approval, with an anticipated start in November 2026.

What You'll Do

  • Build and integrate LLM-enabled capabilities into secure application workflows.
  • Develop or integrate retrieval-augmented generation and agentic-AI components.
  • Design prompts, system instructions, and inference workflows that support real user and mission needs.
  • Connect AI capabilities with existing backend services and decision-support processes.
  • Evaluate outputs for grounding, reliability, accuracy, and usefulness.
  • Develop tests for AI-enabled functionality and support broader integration testing.
  • Demonstrate working prototypes and incorporate technical and user feedback.
  • Document AI designs, workflows, limitations, and implementation decisions.
  • Participate in code reviews, technical reviews, and security-remediation activities.
  • Collaborate with software engineers, security professionals, DevSecOps teams, and customer stakeholders.

What You Bring

  • Four or more years working across AI/ML, large language models, retrieval-augmented generation, and prompt engineering.
  • A master's degree or Ph.D. in AI/ML or a related field.
  • Hands-on delivery of LLM-enabled software and RAG capabilities.
  • Practical knowledge of agentic AI, multi-step workflows, or similar orchestration approaches.
  • Familiarity with building or supporting inference pipelines.
  • The ability to explain your technical contributions, design decisions, and results.
  • Strong collaboration and technical-documentation skills.

Preferred Background

  • A track record of moving AI capabilities beyond coursework, personal projects, or demonstrations into operational software.
  • Practical knowledge of evaluating AI outputs and addressing weak grounding, hallucinations, or unreliable responses.
  • Familiarity with secure software-development and DevSecOps practices.
  • Exposure to classified, restricted, disconnected, or controlled development environments.
  • Collaboration with backend, cybersecurity, and platform-engineering teams.
  • Work supporting defense, government, aerospace, or other regulated environments.
  • Familiarity with containerized OpenShift or Kubernetes environments.

Why Rackner

At Rackner, you will have the opportunity to build technology that supports critical defense and public-sector missions.

You will work on more than isolated AI experiments or prompt-engineering tasks. This role combines hands-on LLM integration, retrieval and agentic-AI development, secure software delivery, and close collaboration across AI, software, cybersecurity, DevSecOps, and mission-focused teams.

Rackner has delivered more than $30 million in recent federal awards and supports mission-critical work across defense, civilian, and public-sector environments. We are looking for an applied AI engineer who can build on that momentum by turning emerging generative-AI capabilities into secure, dependable software with meaningful mission impact.

Benefits & Professional Growth

  • Competitive compensation
  • Company-supported certifications aligned with current and future program work
  • 401(k) with 100% company match up to 6%
  • Medical, dental, vision, life, and disability coverage
  • Paid time off and company holidays
  • Remote-work support and home-office equipment plan
  • Fitness and wellness reimbursement
  • Weekly pay schedule
  • Professional-development and future growth opportunities

Apply

If you are an AI/ML engineer who wants to move beyond standalone prototypes and help integrate LLM, RAG, and agentic-AI capabilities into secure mission software, we would like to hear from you.