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About the Role

Ursa Space is seeking an AI TEVV Engineer to establish how we validate our AI-native geospatial platform. This role focuses on measurement under uncertainty, akin to experimental design and psychometrics, rather than traditional test automation. You will be responsible for the strategy, methodology, and evidence that builds trust in the platform's outputs for both internal stakeholders and customers.

Responsibilities

• Design, develop, and plan the TEVV strategy across the platform's algorithms, AI/ML models, agentic workflows, data pipelines, and analytic products, aligned to the NIST AI RMF Measure function.
• Design statistically defensible evaluations: error metrics and acceptance criteria on representative input distributions, with explicit confidence intervals.
• Define and document the platform's context of use — the validated operating envelope (modalities, geographies, resolutions, conditions, target classes) within which accuracy claims hold.
• Evaluate ground-truth and "golden" datasets, including annotation and adjudication protocols, inter-rater reliability, and quantified uncertainty in the reference data itself.
• Implement a layered evaluation posture: a verifiable core (accuracy, groundedness, format), a rubric-scored middle layer with documented inter-rater reliability, and an honest residual of expert holistic review.
• Evaluate generative and natural-language outputs for claim-level groundedness whether each assertion is traceable to a citable source alongside rubric-based, human-adjudicated assessment.
• Stand up continuous monitoring and re-validation certification gates plus ongoing surveillance watching for model, prompt, retrieval, and agent-behavior drift.
• Author and maintain the TEVV evidence set: test plans, traceability matrices, metrics, acceptance criteria, and credibility-assessment documentation.
• Support DoD AI test-and-evaluation expectations (including DoD Directive 3000.09), contractual milestones, acceptance testing, and demonstrations to government stakeholders.
• Distinguish internal TEVV from organizationally independent IV&V, and partner with external IV&V agents where required.
• Partner with Engineering teams to embed evaluability, observability, and traceability from design onward.
• Contribute to emerging standards (NIST AI TEVV consortium, ISO/IEC SC 42 / 42001), aligning our methodology so evidence packages map to customers' compliance frameworks.
• Perform all other duties as assigned.

Requirements

• B.S. in Computer Science, Statistics, or Systems Engineering, or a related quantitative discipline (M.S./Ph.D. a plus).
• 10+ years of relevant experience, centered on evaluation, measurement, or test-and-evaluation of AI/ML or data-driven systems — not solely software QA or test automation.
• Demonstrated ability to design statistically defensible evaluations: input-distribution design, error-rate estimation, confidence intervals, and context-tied acceptance criteria.
• Hands-on experience building ground-truth/golden datasets — adjudication protocols, inter-rater reliability, and reference-data uncertainty.
• Experience supporting U.S. government contracts (aerospace, defense, or intelligence preferred), including requirements traceability and compliance documentation.
• Working knowledge of the NIST AI RMF and how TEVV evidence maps to customer compliance regimes.
• Strong quantitative skills and Python proficiency for analysis and evaluation (Pandas/Polars, NumPy, ML evaluation libraries).
• Comfort using AI-assisted tools for rapid development and testing.
• Organized and self motivated, able to work successfully with a remote team.
• A creative, flexible mindset for complex problems.
• A fast, reliable internet connection if working remotely.

Skills

• NIST AI RMF
• Python
• Pandas/Polars
• NumPy
• ML evaluation libraries
• AI-assisted tools
• NIST AI TEVV consortium
• ISO/IEC 42001
• ISO/IEC SC 42
• Image and signal processing evaluation
• SAR
• Electro-optical
• RF
• Generative and agentic systems evaluation
• Rubric design
• Human-adjudicated evaluation
• Claim-level groundedness
• V&V/assurance standards (IEEE 1012, DO-178C, ISO/IEC 25010, CMMI)
• Formal IV&V
• GIS tools and libraries
• SpatioTemporal Asset Catalog (STAC)
• NoSQL databases
• SQL databases (Mongo, MySQL, Postgres)
• Test automation
• CI/CD
• pytest
• Jest
• AWS services (S3, Lambda, ECS, ECR, DynamoDB)
• Microservice-based architectures
• Software tooling (Git, Docker, Anaconda, virtual environments)
• Data quality tooling
• Observability tooling
• Monitoring tooling

Location

• Remote (United States)

Work Type

• Fully remote
• Exempt

Experience Level

• 10+ years of relevant experience

Education Level

• B.S. in Computer Science, Statistics, or Systems Engineering, or a related quantitative discipline
• M.S./Ph.D. a plus

Salary/Compensations

• $180,000 - $220,000

Benefits

• Competitive Compensation
• Discretionary PTO & Flexible Scheduling
• Stock Options
• 401(k) Match
• Medical, Dental and Vision Coverage for you and your dependents
• FSA & HSA Plans
• Employer-paid Life Insurance
• Employer-paid LTD and STD for Parental and Family Care
• 11 Paid Holidays
• Employee Resource Groups
• Educational Assistance Program
• Professional Development Opportunities

About the Company

• Ursa Space Systems is building an AI-native geospatial insights platform that guides the acquisition, analysis, and integration of satellite and geospatial data into customer workflows, giving decision makers an edge.
• Leveraging hundreds of data sources, AI agents, and proprietary analytics, Ursa Space provides fast, actionable information to a range of industries, including finance, energy, and defense.
• Our customers receive contextual, comprehensive reporting that goes beyond surface-level observations.

Equal Opportunity

• All applicants and employees who are drawn to serve our mission will enjoy equality of opportunity and fair treatment without regard to race, color, age, religion, pregnancy, sex, sexual orientation, disability, gender identity, gender expression, national origin, genetic information, veteran status, marital status, and prior protected activity.