Senior/Principal Platform Architect (Software, Data and AI)

TeamBuilder is a rapidly growing healthcare SaaS company on a mission to transform healthcare operations through innovative technology. We build solutions that empower healthcare providers to improve patient outcomes, optimize staffing, and operate more efficiently.

We are looking for a Principal Platform Architect (Software, Data & AI) to own and scale the technical foundation across our application, data, cloud, analytics, and AI platforms as TeamBuilder continues to grow.

This role is FULLY REMOTE (U.S. residents only). The ideal candidate is a senior hands‑on technical leader who can build SaaS products in .NET, design enterprise data platforms, own Azure infrastructure, collaborate directly with Data Science, and scale both software systems and data platforms in a cost‑effective, secure, and reliable way.

Role Overview

This is a high-impact senior individual contributor role for someone who thrives at the intersection of software engineering, data architecture, cloud infrastructure, DevOps, analytics, and AI enablement. This person will serve as a technical force multiplier across Product Engineering, Data Science, Analytics, and Operations while helping establish scalable architecture patterns and platform standards.

Key Responsibilities

Enterprise Platform Architecture

• Design and evolve TeamBuilder's platform architecture across application, data, analytics, and AI layers.

• Establish architectural standards and engineering best practices for scalable, secure, and maintainable systems.

• Drive platform modernization initiatives leveraging Microsoft Azure cloud technologies.

• Provide sound recommendations on architectural choices based on technical goals, business needs, and long‑term scalability.

SaaS Product Engineering

• Lead development of scalable SaaS products and services using C#, .NET, ASP.NET Core, SQL, Redis, and related Microsoft technologies.

• Design distributed systems, microservices, APIs, and event‑driven architectures.

• Develop well‑written, documented code in existing and new systems and platforms.

• Partner with Product and Engineering teams to deliver high‑impact features and improve system design.

Data Platform & Analytics

• Architect and evolve enterprise‑scale data warehouse, data lake, and lakehouse environments.

• Design, build, and optimize ETL/ELT pipelines and data integration frameworks.

• Establish data modeling standards, data quality controls, governance practices, and reconciliation processes.

• Support operational reporting, business intelligence, advanced analytics, forecasting, optimization, and AI initiatives.

Cloud Platform, DevOps & Reliability

• Own Azure infrastructure strategy across development, staging, and production environments.

• Design, build, and maintain CI/CD pipelines, deployment automation, and release engineering practices.

• Implement Infrastructure as Code using Terraform, Bicep, ARM templates, or similar tools.

• Improve reliability, observability, security, disaster recovery, performance, and cost efficiency across the platform.

• Support containerized workloads using Docker and Kubernetes/AKS where appropriate.

AI & Data Science Enablement

• Collaborate closely with Data Science to operationalize analytics, AI, and machine learning solutions.

• Design data and infrastructure patterns that support model experimentation, deployment, monitoring, and scale.

• Connect data, applications, infrastructure, and AI use cases into a cohesive platform strategy.

• Research and learn new technologies as needed to deliver technical solutions and enable future product capabilities.

Required Skills / Experience / Qualifications

• 10+ years of software engineering, platform engineering, data engineering, data architecture, DevOps, or related technical experience.

• Expert‑level experience with C#, .NET, ASP.NET Core, SQL, and enterprise SaaS platforms.

• Strong understanding of software engineering design and architectural patterns, including microservices and distributed systems.

• Deep hands‑on experience with Microsoft Azure cloud infrastructure and Azure‑native services.

• Experience designing and implementing enterprise data platforms, including data warehouses, data lakes, lakehouse architectures, and analytical environments.

• Advanced SQL skills with experience optimizing complex queries, pipelines, and large‑scale datasets.

• Strong experience with CI/CD, automation, Git, and modern software delivery practices.

• Experience with Infrastructure as Code, cloud automation, monitoring, observability, and production reliability practices.

• Ability to work cross‑functionally with product owners, data scientists, business users, project managers, engineers, and technical/non‑technical stakeholders.

• Strong written and verbal communication skills with the ability to translate complex technical concepts into clear recommendations.

Nice to Have

• Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Microsoft Fabric, Azure Data Lake Storage, Azure SQL Database.

• Terraform, Bicep, ARM templates, Azure DevOps, GitHub Actions, Docker, Kubernetes, or AKS.

• Power BI data modeling, semantic modeling, performance tuning, and analytics enablement.

• MLOps, AI platform, machine learning, LLM, GenAI, or AI‑assisted operational automation experience.

• Domain‑Driven Design (DDD), event‑driven architecture, distributed event bus, SignalR, Entity Framework, Redis, React, or Next.js.

• Experience in healthcare, workforce management, scheduling, regulated environments, SOC 2, HIPAA‑minded practices, or high‑growth SaaS organizations.

• Experience scaling systems from early‑stage environments to enterprise healthcare deployments.

What Success Looks Like

• Reliable, scalable, and well‑governed application and data platforms that support TeamBuilder's growth.

• Improved developer velocity through clear platform standards, automation, documentation, and reusable architecture patterns.

• Trusted data pipelines and analytical environments that support reporting, analytics, Data Science, and AI initiatives.

• Secure, observable, cost‑efficient Azure infrastructure that supports enterprise SaaS reliability and performance.

• Strong cross‑functional alignment between Product Engineering, Data Science, Analytics, Operations, and business stakeholders.

Culture

We foster a collaborative, engaging, mission‑driven culture that values innovation and prioritizes customer success. This role is ideal for someone who enjoys improving systems, solving complex technical problems, and helping a fast‑moving company scale with clarity and discipline.

Additional Information

• Job Type: Full‑time, Exempt, Fully Remote (U.S. only), minimal travel required.

• Compensation: Competitive, including paid time off, medical benefits, 401k matching, and the potential for an annual performance bonus and/or equity.

• Work Location: Remote.