AI Product Engineer

Assured • New York, NY

116d

About The Position

Assured is transforming the infrastructure of U.S. healthcare using intelligent automation. We’re building an AI-native system of action for provider operations to automate the most painful parts of healthcare, starting with credentialing, licensing, and payer enrollment. These are slow, error-prone processes that cost the healthcare system billions and delay patient care. We’re backed by top Silicon Valley investors and trusted by the most innovative provider groups and health systems. This is a rare opportunity to join an elite team reimagining one of the most broken parts of healthcare - using cutting-edge AI in the real world, at scale. The Role: AI Product Engineer We’re looking for an AI Product Engineer to help architect, build, and productize our AI/ML infrastructure. You'll be the bridge between research, product, customers, and engineering, driving AI adoption from strategy through production at scale. This role is ideal for someone who thrives in early-stage environments, enjoys owning things end to end, and wants their work to have a measurable impact on an industry that desperately needs modern infrastructure.

Requirements

• 3–6+ years experience building and shipping ML or deep learning models in production (or exceptional track record with ~1+ years as first AI/ML hire at a startup)
• Expertise in Python and frameworks like PyTorch, TensorFlow, Hugging Face
• Strong foundation in NLP, deep learning, LLM tools, retrieval pipelines
• Experience with data pipelines (structured/semi‑structured), ETL, cloud infrastructure (AWS/GCP), containerization, and monitoring
• Proven ability to drive architecture and own end-to-end systems delivery
• Great communication—able to explain technical trade-offs to technical and non‑technical audiences

Nice To Haves

• MS/PhD in CS, ML, NLP, or related
• Experience in healthcare, insurance, compliance domains
• Prior experience deploying GenAI/LLM systems with tools such as LangChain, vector DBs, RAG
• Open-source contributions, publications, or technical blog presence

Responsibilities

• Design and engineer the infrastructure for training, serving, and monitoring ML systems (document intelligence, LLM pipelines, compliance inference, risk prediction)
• Establish best practices around reproducibility, model governance, CI/CD, and monitoring
• Lead prototyping, refining, and operationalizing models using deep learning, foundation models, and generative AI
• Optimize pipelines for performance, cost, and scalability
• Partner with product, engineering, and analytics to discover use cases, build features, and deliver value
• Engage with customers to understand operational challenges, validate assumptions, and iterate ML solutions quickly
• Write internal memos, external blogs/whitepapers, and present learnings to elevate Assured’s AI brand

Benefits

• High-impact work - Tackle bottlenecks that slow down provider access to patients
• Real-world AI - Work on meaningful applications of LLMs and applied ML in compliance, forms, automation, and document intelligence
• Cross-functional exposure - Collaborate with customers, clinical ops, engineers, and founders
• Early-stage upside - Equity, early influence, and a high-growth trajectory
• People-first culture - Remote flexibility, mental health time, and a focus on outcomes, not hours

What This Job Offers

• Number of Employees: 101-250 employees