Senior Software Product Engineer (Remote Opportunity)

VetsEZ•Atlanta, GA

85d•Remote

About The Position

At EZ Labs, we are transforming healthcare delivery through technology, innovation, and compassion. We partner with care teams, payers, and providers to improve how patients experience care, how claims are processed, and how care coordination is managed across the continuum. By integrating advanced analytics, intelligent automation, and secure cloud platforms, we enable smarter decisions, seamless patient engagement, and more efficient claims management. Together, we are shaping a healthcare ecosystem that delivers better outcomes for patients, providers, and payers. Position Overview We are seeking a hands-on Product Engineering Lead who uses AI as a catalyst to accelerate development, automate complex workflows, and deliver innovative healthcare solutions. This role blends full-stack engineering expertise, system architecture leadership, and AI-driven product innovation. The ideal candidate is a builder who can rapidly translate concepts into secure, scalable, and production-ready systems that improve patient outcomes and operational efficiency. As a player-coach, you will lead engineers, architect reusable frameworks, and operationalize AI and automation capabilities across our care coordination, claims management, and patient engagement platforms.

Requirements

Bachelor’s Degree in Computer Science, Software Engineering, or related field.
2+ years of software engineering experience, including at least 1 year in a leadership or technical lead role.
Strong proficiency in Python, TypeScript, and Node.js, with deep understanding of cloud-native and event-driven architectures.
Hands-on experience integrating LLMs, intelligent agents, or IDP systems into production environments.
Knowledge of Agent-to-Agent (A2A) and Model Context Protocol (MCP) frameworks.
Proven ability to design and deliver secure, scalable systems using AWS services.
Familiarity with FHIR, HL7, and X12 interoperability standards and healthcare data governance.
Experience using AI-assisted developer tools (GitHub Copilot, Cursor, etc.).
Strong communication and leadership skills with the ability to drive product vision to execution.
Eligibility to obtain a U.S. government clearance (U.S. citizenship required).

Nice To Haves

Prior experience in care coordination, claims processing, or patient engagement systems.
Practical experience operationalizing LLM-based agents or automation pipelines in production.
Background in generative AI integration within secure, regulated environments.
Experience developing microservice patterns and reusable architecture components at scale.

Responsibilities

Architect and Deliver: Design, build, and deploy scalable, AI-enabled microservices using AWS, Node.js, and Python to power healthcare platforms that handle high-volume clinical and claims data.
Accelerate Development: Use AI-assisted tools and LLM integrations (e.g., GitHub Copilot, Cursor, OpenAI, Bedrock, Claude) to reduce development time and increase code quality.
Prototype and Iterate: Rapidly develop, test, and operationalize AI-driven product ideas—such as automated claims triage, intelligent document processing, and conversational assistants—into production-ready features.
Design for Scale: Implement secure APIs, event-driven pipelines, and FHIR-based interoperability patterns supporting healthcare data exchange.
Operationalize Insights: Build APIs and pipelines that convert ML outputs into decision-ready intelligence for clinicians, payers, and operations leaders.
Lead and Mentor: Guide engineers in secure coding, scalable architecture, and AI-integrated development best practices while fostering a culture of experimentation and delivery excellence.
Observability and Reliability: Implement monitoring, logging, and automated alerting (e.g., CloudWatch, Datadog, Prometheus) to ensure system reliability and traceability of AI workflows.
Governance and Compliance: Ensure all AI-enabled components meet HIPAA, VA, and NIST security requirements, aligning with enterprise healthcare standards.
Cross-Functional Collaboration: Partner with clinicians, product managers, and compliance stakeholders to define user needs, translate them into technical designs, and ensure measurable patient and operational impact.
Continuous Improvement: Lead performance tuning, cost optimization, and technical debt reduction initiatives to maintain system quality and agility.
Reusable Frameworks: Develop and maintain shared libraries, SDKs, and automation templates that accelerate AI product delivery across EZ Labs.
Strategic Innovation: Evaluate and recommend emerging AI technologies, frameworks, and cloud services to advance EZ Labs’ modernization roadmap.