Software Architect

An Architect (Engineer IV) is a senior technical leader who shapes and drives the architecture of commercial technologies across the company and is influential across multiple engineering teams. They are a hands‑on technologist who leads by example and coaches engineers in modern, AI‑augmented engineering practices. They are an expert at designing all layers of an application and platform, and they pioneer the use of Agentic AI for architecture, technical design, and implementation—using AI agents to accelerate solution design, generate and review code, evaluate trade‑offs, and automate repetitive engineering tasks. They work in an Agile development environment architecting, designing, leading, and delivering technology solutions to transform healthcare into a safer and more cost‑effective industry. They are expected to be highly in‑tune with industry best practices, emerging AI tooling, technologies, processes, and techniques, and can provide leadership to multiple teams on how to apply them pragmatically to solve business problems. ESSENTIAL DUTIES & RESPONSIBILITIES Software Development Set organization‑wide standards for software structure, maintainability, and quality, including standards for the responsible use of Agentic AI in implementation. Excels in meeting both explicit and implicit user needs. Act as a thought leader in software engineering and AI‑augmented development—designing prompts, guardrails, and agent workflows that accelerate delivery without compromising quality. Teach others to solve problems using multiple languages, technologies, software tools, and AI coding agents. Serve as subject matter expert (SME) in several technologies critical to the organization and contribute to setting organizational standards in technology, methodology, and Agentic AI tooling. Testing & Quality Assurance Master of comprehensive testing strategies that include microservices architecture, API contract testing, and end‑to‑end workflows. Apply Agentic AI to author, expand, and maintain test suites, generate edge‑case scenarios, and triage failures. Provide organizational guidance on testing best practices, including test automation, CI/CD integration, AI‑assisted quality engineering, and metrics tracking. Data Management Partner with other expertise sets to provide prescriptive and anticipatory intelligence. Design solutions that efficiently interact with advanced machine learning tools, generative AI services, and cloud‑based data services. Architect data flows that power Agentic AI use cases (retrieval, grounding, evaluation). Set organizational best practices for data management and is considered a Subject Matter Expert. Infrastructure & Integrations Mastery of cloud architecture, designing and guiding the implementation and adoption of cloud‑native solutions across the organization. Set best practices for cloud service utilization, data migration, complex system integration strategies, and the deployment of AI agents and LLM‑backed services. Provide technical direction and governance on advanced infrastructure and integrations including resource optimization and AI workload cost management. Operations Review analytics to understand user behavior and identify trends in operational metrics to suggest architectural changes. Define organizational strategies for operations, including AI‑assisted observability, incident response, and self‑healing systems. Subject Matter Expert in operational best practices, tools, and techniques. Understand business impact at a macro level and advocate for protecting company reputation. Security & Compliance Direct teams in multi‑stage threat mitigation and secure coding practices, including secure use of Agentic AI (prompt injection defense, model output validation, data governance for AI agents). Develop tools to mediate security holes and offer advanced regulatory compliance guidance, especially as it relates to AI in regulated healthcare contexts (HIPAA, HITRUST). Set the standard for security and compliance within the organization. Product & User Experience Shape the organization's user‑centric direction and champion seamless experiences, including AI‑native interactions where appropriate. Define user interaction patterns for multiple products, fostering consistent experiences. Demonstrate deep expertise in user‑facing technologies, advocating for best practices and innovations. Lead in prioritizing and addressing tech and design debt across the platform. Requirements & Design Set industry standards in crafting functional and non‑functional requirements. Fully understand the path of data. Manage the balance of engineering future and current needs. Set best practices and anti‑patterns for the organization. Apply Agentic AI to accelerate architecture work—generating design alternatives, evaluating trade‑offs, producing ADRs, and reviewing designs against established patterns and constraints. KNOWLEDGE & REQUIREMENTS Highly motivated, self‑learner, and technically inquisitive, with a strong bias toward applying emerging AI tooling to engineering problems. Significant experience creating architecture for complex distributed systems and leading teams through development of those systems. Hands‑on experience using Agentic AI for architecture, technical design, and implementation (e.g., AI coding agents, design copilots, automated code review, RAG‑based design assistants). Capable of leading and/or participating in business, culture, technical, and practice initiatives that support continuous improvement across the organization, including driving adoption of AI‑augmented engineering workflows. Excellent track record of collaborating with stakeholders. Experience proposing new product offerings and contributing to company‑wide strategies using industry knowledge and foresight. Negotiates complex or risky technical business issues on behalf of the company. Consults with management to determine project objectives with long‑term implications. Experience leading technical due diligence and road‑mapping for strategic partnerships, third‑party partners, mergers, and acquisitions. Effective communication and leadership capabilities: capable of communicating strategy and influencing others to align to future state architecture. Expert level experience developing, deploying, and supporting REST services and microservices. Expert level experience with container orchestration platforms and cloud‑native architectures; ability to design and lead adoption of cloud services across major cloud providers regardless of specific platform. Working knowledge of LLM‑backed services, prompt engineering, agent frameworks, evaluation harnesses, and the governance considerations that come with them. Significant experience with relational databases, non‑relational databases, messaging systems, and event‑driven architecture patterns. Expert level experience with containerization technologies and container‑based deployment strategies. Deep expertise in infrastructure as code (IaC) practices to enable repeatable, auditable, and scalable infrastructure. Strong command of service mesh and API gateway patterns for securing and managing microservices at scale. Experience with GitOps and modern continuous delivery practices for cloud‑native platforms. Capable of joining a team to lead initiatives and create software to solve challenging problems. EDUCATION & EXPERIENCE REQUIREMENTS Minimum years of work experience: 8+ years (including demonstrated experience leveraging Agentic AI for architecture, technical design, and implementation) Minimum level of education or education/experience: Bachelor’s or Advanced Degree in related field or equivalent work experience #J-18808-Ljbffr