Evaluate the technical evidence, validation methodology, and reliability of healthcare AI applications for regulatory sandbox pilot deployments. Collaborate with multidisciplinary experts to document findings and provide actionable recommendations regarding AI safety and performance.
You will own the full sales cycle for AI safety solutions, targeting AI builders, labs, and enterprise organizations. This involves building pipeline, conducting consultative discovery, managing complex negotiations, and collaborating with internal teams to ensure successful delivery.
Own positioning, messaging, and sales enablement for mpathic’s AI safety platform and expert-led services, including playbooks, training, competitive materials, and launch readiness. Coordinate go-to-market planning and research, and partner with Sales, Product, Clinical Solutions, and Customer Success to improve customer messaging and feed market insights back into product decisions.
Lead and develop the Program Operations team while building repeatable, customer-centric processes for onboarding, delivery, reviews, renewals, and escalations. Own customer outcomes, executive relationships, retention, and growth, while aligning internal teams and using customer feedback and operational metrics to improve delivery.
Oversee clinical quality across AI safety evaluations, data annotation, and red teaming projects to ensure accuracy and clinical grounding. Develop evaluation rubrics, train clinical experts, and collaborate with cross-functional teams to identify model safety risks.
Design, build, and maintain robust backend systems and scalable cloud infrastructure using .NET and AWS. Collaborate with cross-functional teams to integrate AI models and ensure high performance, reliability, and security across the platform.
The Senior Manager will own and scale the company's compliance and audit programs, including SOC 1, SOC 2, ISO 27001, and FDA 21 CFR Part 11 certifications. They will partner with engineering and operations teams to automate evidence collection, manage internal audits, and ensure robust AI governance.
Design, develop, and maintain intuitive user interfaces for AI-powered web applications while ensuring high performance and accessibility. Collaborate with cross-functional teams to integrate RESTful APIs and translate complex data into actionable product experiences.
The Program Manager will lead the execution of complex AI safety, evaluation, and human data programs by coordinating cross-functional teams and managing end-to-end delivery. They will act as the connective tissue between technical, clinical, and operational teams to ensure high-quality, auditable, and scalable project outcomes.
The Program Manager will lead end-to-end delivery of complex AI safety and human data operations, managing cross-functional teams and customer engagements. They are responsible for establishing project plans, ensuring quality standards, and acting as the primary point of contact for stakeholders.
The role involves collaborating on AI safety initiatives by roleplaying clinical scenarios, identifying behavioral edge cases, and providing expert feedback on mental health policy. You will also design testing scenarios, conduct qualitative analysis, and develop behavioral taxonomies to ensure accurate AI responses to psychological distress.
Evaluate and improve AI models supporting clinical operations and administrative workflows to ensure accuracy and practical application. Review real-world healthcare scenarios and provide expert feedback on AI-generated responses regarding EHRs and regulatory standards.
Design and evaluate clinically realistic tasks to benchmark multimodal AI systems in the radiology domain. Provide expert reference answers and detailed feedback to improve AI diagnostic reasoning and instruction-following.
Design expert-level cybersecurity prompts and evaluate AI-generated responses for technical accuracy and safety. Provide actionable feedback to improve the reliability and security of frontier AI systems.
Design realistic clinical scenarios and evaluate AI-generated responses to ensure clinical accuracy and safety. Provide actionable feedback to improve the reliability and trustworthiness of healthcare AI models.
Evaluate AI-generated prior authorization recommendations and specialty medication requests for accuracy and alignment with payer requirements. Provide actionable feedback to improve AI performance on complex pharmacy authorization workflows.
Design clinically realistic psychiatric scenarios and prompts to test and improve the reasoning of large language models. Evaluate AI-generated responses for accuracy and safety while providing structured feedback to researchers.
