Senior Applied AI Engineer

About the role

The Senior Applied AI Engineer will build and ship production AI systems end to end, from problem definition to deployment and iteration. They will develop AI agents and workflow automation systems that can reason over context, use tools, and integrate with internal platforms. They will partner with Engineering, Product, Data, and Operations to integrate AI capabilities into Abby Care's products and internal systems. They will also improve reliability, observability, guardrails, and human-in-the-loop review mechanisms for production AI systems.

Responsibilities

• Build and ship production AI systems end to end, from problem definition to deployment and iteration.
• Develop AI agents and workflow automation systems that can reason over context, use tools, and integrate with internal platforms.
• Design evaluation frameworks, datasets, metrics, and feedback loops to measure and improve AI system quality.
• Apply LLMs, multimodal models, RAG, structured extraction, and tool use to real-world healthcare workflows.
• Partner with Engineering, Product, Data, and Operations to integrate AI capabilities into Abby Care’s products and internal systems.
• Improve reliability, observability, guardrails, and human-in-the-loop review mechanisms for production AI systems.
• Stay close to frontier AI capabilities and apply them pragmatically to create business and operational leverage.

Requirements

• 5+ years of software engineering, applied AI, machine learning, or related technical experience.
• Strong experience building and shipping production software systems.
• Hands-on experience with modern AI systems, including LLMs, RAG, agents, structured extraction, classification, or workflow automation.
• Strong programming skills and ability to work across backend systems, APIs, data pipelines, and AI orchestration layers.
• Practical experience with prompt engineering, tool use, retrieval, model selection, context management, and failure analysis.
• Experience designing evaluation methodologies for AI systems, including quality metrics, test sets, human review loops, and error analysis.
• Strong system design judgment around reliability, scalability, observability, and maintainability.
• High ownership, strong execution, and comfort operating in a fast-paced startup environment.

Preferred Experience

• Built agentic systems, AI copilots, or workflow automation in production.
• Experience with multimodal AI, OCR, document understanding, or structured data extraction.
• Experience in healthcare, insurance, caregiving, or other regulated and operations-heavy domains.
• Experience with human-in-the-loop systems, auditability, and quality assurance workflows.
• Experience with knowledge graphs, ontologies, entity resolution, or structured knowledge representation.
• Prior startup or zero-to-one product development experience.