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Principal Architect, AI-Native Applications

Full-time
Lead
150k to 200k (currency not captured)
Posted 2 months ago
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Where you can work

Unspecified

Locations named in the listing

  • New Jersey, United States
  • Newark, New Jersey, United States
View location wording from the posting
  • ark, New Jersey
  • Newark, New Jersey, United States

Employer description

WebMD Ignite, a division of WebMD and Internet Brands, is the growth partner for healthcare organizations. We guide people to better health at all stages of their journey, from discovery to recovery. Our combination of leading brands in the industry—including WebMD, Medscape, Krames, PulsePoint, Vitals, The Wellness Network, Mercury Healthcare, and Healthwise—offers comprehensive solutions that engage individuals with timely, relevant messaging that optimizes experiences and outcomes, driving loyalty and lifetime value for our clients. Learn more at WebMDIgnite.com.

WebMD Ignite, a division of WebMD and Internet Brands, is the growth partner for healthcare organizations. We guide people to better health at all stages of their journey, from discovery to recovery. Our combination of leading brands in the industry — including WebMD, Medscape, Krames, PulsePoint, Vitals, The Wellness Network, Mercury Healthcare, and Healthwise — offers comprehensive solutions that engage individuals with timely, relevant messaging that optimizes experiences and outcomes, driving loyalty and lifetime value for our clients. Learn more at WebMDIgnite.com.

About the Role:

The Principal Architect, AI-Native Applications is the lead technical authority for how WebMD Ignite designs, builds, and scales modern applications in an AI-native environment. This role defines the architectural patterns, standards, and reference implementations that development teams across the organization build against, with a particular focus on backend systems, data-intensive services, and applications that embed large language models, retrieval-augmented generation, and agentic workflows. The Principal Architect operates as a hands-on individual contributor and technical leader, remaining close enough to the code to pair with senior engineers and validate design decisions directly. This is a senior, cross-cutting role that establishes a coherent application architecture practice where design decisions are currently made project by project.

Key Responsibilities:

  • Define and own the application architecture patterns, standards, and reference implementations that development teams build against across the organization.
  • Architect complex backend systems, including microservices architectures, APIs, streaming and event-driven protocols, and data engineering pipelines.
  • Design high-performance data platforms for AI workloads, including vector stores, graph databases, distributed caching, and semantic retrieval over million-record corpora.
  • Establish the patterns and guardrails for AI-native applications, including LLM integration, retrieval-augmented generation, multi-model orchestration, and agentic workflows.
  • Conduct architecture reviews and ensure solution designs meet scalability, performance, security, interoperability, and cost requirements across both cloud and on-premises environments.
  • Set standards for AI-ready APIs, data services, and application frameworks that enable rapid prototyping and production rollout of new capabilities.
  • Partner with engineering, product, data, and DevOps leaders to align technical direction with business outcomes and delivery timelines.
  • Ensure architectures meet the security, compliance, and privacy requirements of regulated healthcare environments, including HIPAA and the handling of protected health information (PHI).
  • Provide technical mentorship to senior engineers and raise the overall architecture fluency of the engineering organization.

Qualifications:

  • 7+ years of experience in software architecture, backend engineering, or data engineering, including senior or principal-level technical leadership.
  • Demonstrated experience architecting complex, distributed backend systems using microservices, APIs, and event-driven or streaming patterns.
  • Hands-on experience designing and operating data platforms for high-volume, high-dimensional workloads, including vector databases, graph databases, distributed caching, and semantic retrieval.
  • Practical experience building AI-native or AI-enabled applications, including LLM integration, retrieval-augmented generation, orchestration frameworks, and agentic systems.
  • Strong command of cloud architecture (AWS, Azure, or GCP) and experience operating across both cloud and on-premises environments.
  • Ability to remain hands-on in code while providing architecture-level leadership.
  • Working knowledge of the security, privacy, and compliance requirements of healthcare data environments, including HIPAA and PHI handling.
  • Excellent communication skills, with the ability to translate complex technical concepts for both engineering and business audiences.

Preferred Skills:

  • Experience in a healthcare, health IT, or other regulated data environment.
  • Experience operating within HITRUST, NIST, or similar compliance frameworks.
  • Familiarity with modern warehouse/lakehouse and high-performance analytical data platforms.
  • Experience defining developer tooling, standards, and AI-assisted software development workflows.

Compensation: $150,000 - $200,000

Bonus Eligible:

This position is also eligible for a discretionary company bonus, based upon business results.

Benefits:

Employees in this position are eligible to participate in the company sponsored benefit programs, including the following within the first 12 months of employment:

  • Health Insurance (medical, dental, and vision coverage)
  • Paid Time Off (including vacation, sick leave, and flexible holiday days)
  • 401(k) Retirement Plan with employer matching
  • Life and Disability Insurance
  • Employee Assistance Program (EAP)
  • Commuter and/or Transit Benefits (if applicable)

Eligibility for specific benefits may vary based on job classification, schedule (e.g., full-time vs. part-time), work location and length of employment.

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