Applied AI Product Engineer

Role Overview

• Design, develop, and implement AI-powered features across healthcare product platforms and operational systems.
• Build full-stack applications using modern AI engineering workflows and tools such as Cursor, Claude, Codex, OpenAI APIs, and related LLM technologies.
• Collaborate with product managers, designers, engineers, and clinical stakeholders to deliver scalable, user-focused solutions that improve patient engagement, care coordination, and operational efficiency.
• Develop APIs, backend services, automation pipelines, and AI workflows that support intelligent product capabilities and production-ready deployments.
• Apply software engineering, DevOps, and MLOps best practices to testing, deployment, monitoring, and optimization of AI solutions.
• Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks to continuously improve platform capabilities.
• Navigate ambiguity, solve complex technical challenges, and collaborate effectively across technical and non-technical teams in a fast-paced Agile environment.
• Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical discipline.
• 2+ years of professional experience in software engineering, product engineering, or full-stack application development.
• Hands-on experience delivering at least 2–3 production-level AI projects using tools such as Cursor, Claude, Codex, OpenAI, Anthropic, or similar AI development platforms.
• Strong programming skills with proficiency in Python, TypeScript, JavaScript, or related modern development languages, along with experience building and deploying production-grade full-stack applications.
• Experience integrating large language models (LLMs), prompt engineering, AI agents, generative AI workflows, or retrieval-augmented generation (RAG) architectures.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform, along with containerization and deployment technologies such as Docker and Kubernetes.
• Strong communication, collaboration, analytical, and problem-solving skills with the ability to work independently in a remote Agile environment.
• Additional Qualifications: Experience with AI-assisted software development workflows, vector databases, embeddings, semantic search, orchestration frameworks, or AI workflow automation.
• Familiarity with machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, or scikit-learn.
• Exposure to CI/CD pipelines, DevOps practices, infrastructure automation, or secure healthcare technology environments.
• Experience supporting healthcare, payer/provider, federal government, or Department of Veterans Affairs (VA) technology initiatives is preferred.
• Ability to obtain a government clearance is a plus.

Tech Stack

• AWS
• Azure
• Cloud
• Docker
• Google Cloud Platform
• JavaScript
• Kubernetes
• Python
• PyTorch
• Scikit-Learn
• Tensorflow
• TypeScript

Benefits

• Medical/Dental/Vision.
• 401k with Employer Match.
• PTO + Federal Holidays.
• Corporate Laptop.
• Training opportunities.
• Remote Opportunity.