Senior AI Engineer
The responsibilities include building agent-driven enrollment and parent communication pipelines that scale significantly without proportional headcount growth; creating and managing parallel simulations of students testing curriculum to identify gaps and generate improvements; developing automated culture and community agents for engagement, onboarding, and retention at machine scale; constructing real-time operational dashboards to provide leadership with visibility into various business aspects such as enrollment, academic progress, parent satisfaction, and campus operations; designing AI-first workflows for guides, advisors, and operational staff to reduce administrative burdens and refocus on students; building systems called Brainlifts to capture and compound institutional knowledge over time; and integrating these capabilities into Alpha's broader AI ecosystem including EPHOR, Alpha GPTs, and Fleet/Swarm infrastructure.
AI QA Analyst
Review and annotate complex conversation traces to rate response quality based on metrics such as helpfulness, honesty, and harmlessness (HHH). Build and maintain high-quality "Golden Datasets" and benchmarks to stress-test the model across various domains and edge cases. Conduct pre-deployment testing and A/B model comparisons to identify performance regressions or improvements. Categorize model failures (hallucinations, logic errors, tone drift) to provide actionable feedback to the Engineering and Research teams. Help define and refine the rubric for "what a good response looks like" as the product evolves.
Research Engineer – Matilda
Contribute to building Matilda, a conversational AI platform, by engaging in a variety of tasks including researching relevant literature, developing telemetry systems for production infrastructure at scale, and other related activities as needed. Work collaboratively within a small team that values fast progress and takes the work seriously. Adapt to various roles and responsibilities as they arise without a fixed detailed job specification.
Clinical AI Engineer
Build end-to-end AI features by architecting and shipping fullstack solutions from React frontends to Python backend services that leverage voice AI and large language models to automate clinical workflows; implement and fine-tune audio processing pipelines ensuring accurate performance of Automatic Speech Recognition (ASR) and LLM agents in diverse medical environments; translate complex clinical feedback into technical solutions by rapidly prototyping and deploying improvements to model behavior, prompting strategies, and audio handling; optimize fullstack performance for real-time audio streaming and token generation to minimize latency for seamless clinician interaction; partner with implementation and clinical teams to shorten the feedback loop by shipping critical integrations and feature requests from concept to production quickly.
Data Strategy Associate
Design and build intuitive web interfaces for robot data annotation, datasets visualization, and experiment tracking. Utilize data-driven techniques to optimize interfaces for efficiency and fast iteration cycles. Integrate AI models to automate manual tasks. Work together with AI researchers, robot operators, and annotators to support new user experiences.
Freelance Web Scraping Engineer (Vibe Coding)
Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets. Leverage internal tools (Apify, OpenRouter) alongside custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements. Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior. Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery. Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.
DevOps Engineer, Infrastructure & Security
The role involves taking full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Responsibilities include overseeing the end-to-end health of the platform to ensure seamless integration between the AI core and all full-stack components, from APIs to UI, maintaining a responsive and production-ready environment. The job also requires building automated systems to monitor model performance and data drift across geographically dispersed environments, managing the technical lifecycle within diverse regulatory frameworks, leading the response for production issues in mission-critical environments, ensuring rapid resolution and prevention of future issues. Additionally, the role requires translating deep technical performance metrics into clear insights for senior international government officials and partnering with Engineering and ML teams to ensure lessons learned in the field influence the technical architecture and decisions of future use cases.
Field Engineering Manager, Public Sector
As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, support end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and resilient cloud infrastructure for international government partners. Responsibilities include owning the production outcome with full accountability for long-term performance and reliability of AI use cases across international government agencies, ensuring full-stack integrity by overseeing all platform components from APIs to UI for a production-ready environment, building automated systems to monitor model performance and data drift across dispersed environments, managing the technical lifecycle within diverse regulatory frameworks, leading incident response in mission-critical environments with rapid resolution and prevention guardrails, translating technical performance metrics into clear insights for senior government officials, and partnering with engineering and ML teams to influence the technical architecture and decisions for future AI use cases.
Senior Systems Performance Engineer
The Senior Systems Performance Engineer at Crusoe is responsible for leading the evaluation and establishment of New Product Introduction (NPI) across varied hardware architectures with a focus on Bare Metal and VM environments. They conduct deep-dive performance evaluations and workload characterizations across compute, memory, storage, and networking. They develop sophisticated multi-variable projection models and frameworks to analyze system design options through tradeoffs such as Power and Total Cost of Ownership (TCO). The role involves collaborating with external vendors to drive platform customization and optimize server and AI architectures for maximum performance-per-TCO. They design and implement performance methodologies to scale evaluation processes for large-scale GPU/AI data centers. Additionally, they engage in industry research and contribute technical insights to consortiums and standards committees to influence future hardware roadmaps.
Expansion Account Executive
Debug and fix issues in the platform and ship pull requests with fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concepts for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.
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