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

FM Talent Source

Lead Software Engineer

Silver Spring, MD · On-site

$113 - $188/hr

Utilize Generative AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) for code generation, debugging, testing, refactoring, and documentation while ensuring code quality and ...

SMX

Cleared Hybrid QA Tester/Engineer (5416)

Hanover, MD · On-site

$41 - $56/hr

Experience testing AI-powered applications, generative AI integrations, or machine learning systems * Experience testing cloud-native applications deployed in AWS environments * Familiarity with CI ...

Tata Consultancy Service Limited

Engineer

Owings Mills, MD · On-site

$80K - $90K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Experience developing and implementing generative AI models, with a understanding of deep learning ... Experience in DevOps. CI/CD and testing framework is plus TCS Employee Benefits Summary:

SMX

Cleared Hybrid QA Tester/Engineer (5416)

Hanover, MD · On-site

$40.75 - $55.50/hr

... testing AI-powered applications, generative AI integrations, or machine learning systems • Experience testing cloud-native applications deployed in AWS environments • Familiarity with CI/CD ...

State of Maryland

Senior AI Developer

Baltimore, MD · On-site

$60.79 - $80.21/hr

  • Dental

  • Life

Establish and apply ITB's AI application development standards: code quality, testing ... tools, generative AI, or applied machine learning) * Experience deploying and maintaining ...

Under Armour, Inc.

Sr. Data Analytics Engineer

Baltimore, MD · On-site +1

$125K - $165K/yr

  • Medical

  • Retirement

Apply Generative AI tools to streamline development workflows and enhance product quality ... modeling, testing, documentation, governance) or equivalent. * 2+ Years of experience & strong ...

Under Armour

Sr. Data Analytics Engineer

Baltimore, MD · On-site +1

$125K - $165K/yr

  • Medical

  • Retirement

Apply Generative AI tools to streamline development workflows and enhance product quality ... modeling, testing, documentation, governance) or equivalent. * 2+ Years of experience & strong ...

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Generative Ai Testing information

See Baltimore, MD salary details

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How much do generative ai testing jobs pay per hour?

As of Aug 17, 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 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 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.

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 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 do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

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

Lead Software Engineer

FM Talent Source

Silver Spring, MD • On-site

$113 - $188/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Lead Software Engineer

Non-SCA, Full-time US

2 days ago Requisition ID: 1742

Salary Range: $113,000.00 To $188,000.00 Annually

FM Talent Source is an enterprise that provides business and workforce solutions to help organizations nationwide overcome business challenges. Our clients include federal, state and local government agencies, Fortune 500 Companies, and non-profit organizations. Founded in 2004, we have a strong history of providing recruitment strategies and utilizing effective project and quality management methodologies to ensure our clients success.

We are seeking one Lead AI Software Engineer for a full-time contract opportunity with FM Talent Source for one of our valued clients.

This role is ideal for a senior technologist who is passionate about building scalable, secure, and user-centric AI-enabled solutions to address complex government mission challenges.

You will lead the design, development, and deployment of full-stack web applications on AWS, integrating workflow orchestration, relational data systems, advanced analytics, and intuitive, accessible user interfaces. Working with cross-functional teams—including software engineers, data scientists, product managers, and mission stakeholders—you will deliver high-impact solutions that combine modern engineering practices with Artificial Intelligence capabilities.

This role emphasizes hands-on leadership, strong engineering fundamentals, and modern software development practices—including the use of Generative AI-assisted codingtools to accelerate development, improve quality, and enhance delivery velocity.

RESPONSIBILITIES

  • Lead the architecture, design, and implementation of AI-enabled full-stack web applications deployed on AWS.
  • Develop and maintain end-to-end solutions spanning frontend (ReactJS), backend services (Java/Python), APIs, workflow orchestration, and relational database layers.
  • Design and implement accessible, user-friendly web interfaces, ensuring compliance with Section 508 and usability standards.
  • Architect and manage RDBMS-based data models (e.g., PostgreSQL, MySQL, Aurora) supporting transactional and analytical use cases.
  • Build and integrate workflow and process automation capabilities to support business and mission operations.
  • Develop data visualization and analytics features to enable decision-making through dashboards, charts, and interactive UI components.
  • Lead implementation of AI-enabled features such as intelligent search, chatbots, document processing, or agent-driven workflows.
  • Utilize Generative AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) for code generation, debugging, testing, refactoring, and documentation while ensuring code quality and security.
  • Operate within a SAFe (Scaled Agile Framework) environment, contributing to agile release trains, sprint planning, backlog refinement, and cross-team coordination.
  • Implement and enforce DevSecOps practices, leveraging application security tools (e.g., SAST, DAST, SCA) to identify, analyze, and remediate software vulnerabilities throughout the development lifecycle.
  • Design and maintain CI/CD pipelines with integrated security scanning, automated testing, and compliance checks.
  • Mentor engineering teams, conduct code reviews, and establish best practices in software design, security, and cloud-native development.
  • Collaborate with cross-functional teams to prototype, iterate, and deliver scalable and secure solutions aligned to mission requirements.

QUALIFICATIONS

  • Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.
  • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or Additional FOUR (4) years equivalent experience in Lieu of degree.
  • Minimum SIX (6) years of professional experience in software engineering, including experience in a senior or lead role.
  • Expert-level proficiency in Java or Python for backend development.
  • Strong hands-on experience with ReactJS for modern frontend application development.
  • Demonstrated experience building and deploying full-stack web applications in AWS cloud environments.
  • Experience implementing solutions involving workflow orchestration, relational databases (RDBMS), and data visualization.
  • Experience designing and developing accessible web user interfaces, including familiarity with accessibility standards and testing tools.
  • Experience designing and integrating RESTful APIs, microservices architectures, and distributed systems.
  • Hands-on experience with Generative AI-aided coding and software development tools to improve productivity, code quality, and delivery efficiency.
  • Experience working within a SAFe (Scaled Agile Framework) environment.
  • Experience using application security and DevSecOps tools to identify, analyze, and remediate vulnerabilities across the software development lifecycle (e.g., SAST, DAST, SCA, container and dependency scanning).
  • Experience implementing CI/CD pipelines, automated testing, version control, and secure coding practices.
  • Strong leadership, communication, and collaboration skills, with the ability to lead technical teams and engage stakeholders effectively.

PREFERRED EXPERIENCE:

  • Experience developing AI/ML applications, such as Retrieval-Augmented Generation (RAG), chatbots, semantic search, or agentic workflows.
  • Familiarity with AI frameworks such as LangChain, Haystack, Semantic Kernel, or similar.
  • Experience with AWS services such as Lambda, ECS/Fargate, API Gateway, Step Functions, S3, and Glue.
  • Experience with modern data architectures, including lakehouse, federated query engines, or analytics platforms.
  • Experience with data visualization tools and libraries (e.g., D3.js, Plotly, Tableau, QuickSight).
  • Familiarity with Infrastructure as Code (Terraform, AWS CDK, CloudFormation).
  • Knowledge of federal security and compliance standards (FISMA, FedRAMP, NIST 800-53).
  • SAFe certification or additional Agile certifications.
  • Experience mentoring teams and driving adoption of secure, AI-enabled, cloud-native development practices.

Compensation Range: The salary range provided is determined by market value, internal equity, and the candidate's experience and qualifications. Offers will be extended within this range, though not all candidates will receive an offer at the upper limit.

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