Engineering Lead

Assured • New York, NY

119d

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.

Requirements

• 8+ years of experience designing and scaling distributed systems and SaaS platforms in regulated environments (e.g., healthcare, finance).
• Proven expertise in microservices architecture, asynchronous messaging systems, and container orchestration using Kubernetes.
• Proficiency in modern programming languages (e.g., Node.js, Go, Python) and infrastructure-as-code tools (e.g., Terraform, Pulumi).
• Demonstrated leadership in implementing AI/ML and GenAI solutions in production.
• 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 enterprise-grade systems.
• Open-source contributions, publications, or technical blog presence.

Responsibilities

• Design and evolve a modular microservices-based architecture with clear domain boundaries and scalable APIs.
• Lead the adoption of publish/subscribe (pub/sub) patterns for real-time, decoupled communication using platforms such as Kafka or Amazon SQS.
• Architect systems to support high availability, disaster recovery, and performance optimization at scale.
• Define cloud infrastructure architecture using AWS, GCP, or Azure, with a focus on security, scalability, and automation.
• Lead the strategy, design, and integration of Generative AI and Machine Learning capabilities to enhance clinical decision support, automate operational workflows, and personalize user experiences.
• Evaluate AI tools, frameworks, and third-party APIs, ensuring alignment with platform goals and data protection requirements.
• Provide architectural guidance across teams and ensure adherence to engineering best practices throughout the SDLC.
• Mentor software engineers, promote a culture of technical ownership, and facilitate design reviews and documentation.
• Guide teams in deploying scalable, observable, and resilient services with CI/CD pipelines, infrastructure-as-code, and monitoring tools.
• Champion best practices for system security, auditability, and privacy by design.
• Lead efforts in incident response readiness, chaos engineering, and platform reliability.
• Act as a technology advisor to product managers, business leaders, and clinical stakeholders.
• Translate complex business requirements into scalable technical solutions that align with product vision and regulatory standards.

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