Senior AI Engineer, Slingshot Aerospace

• 6+ years of experience in software engineering, machine learning engineering, applied AI, or equivalent experience
• Strong Python engineering skills with experience building SDKs, libraries, or evaluation tooling
• Experience designing evaluation frameworks, benchmarks, metrics, or test harnesses for AI/ML systems
• Ability to analyze system behavior, identify failure modes, and evaluate performance in complex autonomous or semi-autonomous systems
• Familiarity with modern agent frameworks, orchestration patterns, or protocol-based integrations
• Experience working in cross-functional, multidisciplinary teams
• Strong written and verbal communication skills
• Bachelor’s degree in a relevant science or engineering field, or equivalent experience
• Must be a U.S. citizen and eligible to obtain and maintain a government security clearance

Desirable

• As a Senior AI Engineer focused on Agentic Evaluation and Verification and Validation (V&V), you will join the AI and Data Science team within Slingshot’s Research and Development organization
• You will contribute to advancing how intelligent systems are evaluated and validated for mission-critical space operations
• This role focuses on building and scaling evaluation frameworks, benchmarks, and simulation-backed validation systems for agentic AI systems, including multi-step, tool-using, and autonomous decision-making workflows powered by LLMs and reinforcement learning
• Your work will directly support the development of reliable and trustworthy autonomous mission planning systems
• You will partner closely with AI researchers and domain experts to translate real-world mission concepts into structured, testable evaluation systems
• Extend and maintain Slingshot’s V&V SDK and evaluation framework for simulation-backed validation of agentic AI systems
• Design and implement agent-level and end-to-end evaluations, including benchmark scenarios, scoring logic, and experiment harnesses
• Build benchmark scenarios and tooling that measure planning, reasoning, and operational performance for autonomous mission planning systems
• Translate astrodynamics and mission-domain concepts into executable evaluation scenarios and simulation configurations
• Develop reusable SDK interfaces, adapters, and evaluation utilities that connect V&V systems, TALOS benchmarks, and agent workflows
• Define and apply metrics for capability evaluation, failure analysis, regression detection, and comparative benchmarking
• Partner with cross-functional teams to identify evaluation needs and contribute to improving coverage of critical capabilities
• Contribute to best practices for evaluating complex, autonomous AI systems
• Uphold strong engineering standards through testing, documentation, reproducibility, and maintainable system design