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Generative Ai Testing Jobs in Washington (NOW HIRING)

LOGC2

EOIR Program Manager - AI TESTING

Springfield, VA · On-site

$121K - $121K/yr

Lead and guide the work of technical staff executing complex AI Testing, Evaluation, Verification, and Validation (TEVV) activities, including generative AI performance assessments and adversarial ...

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Generative Ai Testing information

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 Washington?

For Generative Ai Testing jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Washington look for?

The top searched job categories for Generative Ai Testing jobs in Washington are:

What cities in Washington are hiring for Generative Ai Testing jobs?

Cities in Washington with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 8% Part Time, 2% Temporary, 7% Contract, and 1% Nights. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution.

EOIR Program Manager - AI TESTING

LOGC2

Springfield, VA • On-site

$121K - $121K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago

Job description

Description:

Contingent on Contract Award

National Capital Region (Hybrid On-site/Telework)

Current on-site location is in Alexandria, VA (Relocating to Falls Church, VA in Q2 2027)


Connected Logistics is seeking a highly skilled and versatile Program Manager, EOIR to lead a critical Artificial Intelligence (AI) Testing, Evaluation, Validation, and Deployment Readiness Services contract for the Department of Justice (DOJ) Executive Office for Immigration Review (EOIR). This is a high-visibility Key Personnel role that requires a unique blend of executive-level program management and deep technical expertise in AI evaluation and risk management.

The ideal candidate will plan, initiate, and manage this complex information technology project, serving as the primary liaison between the business and technical aspects of the EOIR mission. Simultaneously, they will lead a technical staff utilizing a FedRAMP-authorized cloud platform to conduct independent testing, adversarial red teaming, and Independent Verification and Validation (IV&V) of Generative AI, Large Language Models (LLMs), and machine learning models.


Key Responsibilities:

  • Program & Contract Management: Plan, initiate, and manage all IT/AI project activities across SOW Task Areas 1-5. Monitor progress continuously to ensure deadlines, quality standards, and Firm-Fixed-Price (FFP) cost targets are met.
  • Technical Leadership: Lead and guide the work of technical staff executing complex AI Testing, Evaluation, Verification, and Validation (TEVV) activities, including generative AI performance assessments and adversarial red teaming.
  • Stakeholder Liaison: Serve as the primary liaison between the business and technical aspects of the project. Ensure contract staff seamlessly integrate and collaborate with other EOIR department contract staff (e.g., Software Development and Program Office Support).
  • Methodology & Quality Assurance: Plan project stages and assess business implications for each stage using a disciplined program management methodology covering risk management and configuration management. Implement the Quality Control Plan (QCP) to identify, prevent, and ensure non-recurrence of defective services.
  • Deliverable Management: Lead the development and timely submission of all contract deliverables, including the Task Order Management Plan, Transition-In/Out Plans, AI Test and Evaluation Plans, and Monthly Contract Status Reports.
  • Workforce & Telework Management: Maintain an adequate, stable workforce for uninterrupted performance. Manage work assignments and submit detailed monthly telework reports to the Government Task Monitor (GTM) detailing hours, duties accomplished, and reporting frequencies.
  • Security & Compliance: Ensure all contractor-provided platforms adhere to Federal, DOJ, and EOIR security requirements, including FISMA, NIST SP 800-53, and NIST AI RMF, and support necessary Authority to Operate (ATO) processes.
  • Establish technical standards for data operations, development, interoperability, performance, and access-control implementation consistent with Government requirements.
  • Lead assessments and improvements to enterprise search and unstructured-data discovery capabilities while operating within applicable access-control and DOJ security requirements.
Requirements:
  • Bachelor’s degree in Computer Science, Information Technology, Engineering, Business, or a related field, accompanied by 8+ years of progressive experience planning, initiating, and managing information technology (IT) projects. Federal Government contracting experience is highly preferred.
  • Must be able to obtain and maintain a DOJ Public Trust level security clearance (candidates with an active or recently active Tier 2 or higher clearance are strongly preferred).
  • Project Management Certification: Active Project Management Professional (PMP) certification is required.
  • Technical Certifications: Must hold at least one relevant technical certification demonstrating competence in AI, Cloud, or Cybersecurity, such as:
  • AWS Certified Machine Learning–Specialty / Azure AI Engineer Associate
  • Certified Information Systems Security Professional (CISSP) or Certified Information Security Manager (CISM)
  • ISTQB Certified Tester (Advanced Level) or equivalent QA/Testing certification
  • Microsoft Certified: Azure Data Engineer Associate” retired on March 31, 2025. Replace it with the following:
  • Microsoft Certified: Fabric Data Engineer Associate
  • Microsoft Certified: Azure Solutions Architect Expert
  • AWS Certified Data Engineer - Associate
  • AWS Certified Solutions Architect
  • Certified Data Management Professional
  • Domain Expertise Demonstrated understanding of Artificial Intelligence (AI) technologies, including LLMs, Retrieval-Augmented Generation (RAG), machine learning, and AI red teaming methodologies.
  • Regulatory Knowledge Familiarity with the NIST AI Risk Management Framework (RMF), FedRAMP cloud environments, and Federal IT security/ATO processes.



Total Rewards Statement


We believe in fairness and clarity throughout our hiring process. The anticipated salary range for this position is $150,000.00-160,000.00 USD. This is a good-faith range based on factors such as your experience, geographic location, and any applicable contractual requirements, and may vary slightly.


Beyond salary, we provide a robust benefits package and encourage ongoing professional development, because your growth and well-being matter to us. We’re excited to support you in building a rewarding career with us!


Connected Logistics respects the need for confidentiality for all applicants.


Connected Logistics has been named a 2026 WTOP Top Workplace in the medium sized business category. Our mission is clear: we deliver mission-focused IT, cybersecurity, logistics, and enterprise modernization support to federal agencies. When we invest in our people and create an environment where they feel valued and empowered, we deliver stronger outcomes for our clients and the missions we support.


Connected Logistics offers an excellent benefits package that includes health, dental, vision, life, and disability insurance, a great 401(k) package, and generous Paid Time Off.


EOE/Disability/Veterans