You will make an impact:

The Principal Software Architect will lead the design and evolution of AI-enabled software platforms, helping translate business and product needs into scalable, secure, and responsible technical solutions. This role partners closely with software engineers, product teams, data specialists, and business stakeholders to identify opportunities for AI, guide architecture decisions, review implementations, and mentor teams on modern engineering practices, AI-assisted development, and sound design principles.

Your day to day:

• Research emerging AI, machine learning, generative AI, cloud, and software architecture technologies and evaluate their fit for the product platform

• Analyze existing features, data flows, and system designs for scalability, performance, security, and AI-readiness in order to design and recommend solutions

• Document current and future architectural patterns, including AI integration patterns, model lifecycle considerations, data governance, observability, and responsible AI guardrails

• Communicate complex AI, data, and architecture concepts clearly to technical and cross-functional colleagues

• Define reference architectures for AI-enabled capabilities, including data ingestion, retrieval-augmented generation, model integration, inference services, monitoring, and human-in-the-loop workflows

• Promote responsible AI practices, including privacy, security, explainability, bias mitigation, regulatory awareness, and appropriate use of enterprise data

• Guide teams in the effective use of AI-assisted engineering tools to improve productivity, code quality, documentation, testing, and delivery velocity

AI & Modern Engineering Focus

We're actively incorporating AI-powered capabilities into our platform, and you'll help shape how this is done responsibly and effectively in an enterprise environment. This includes:

• Integrating LLMs and AI services into .NET- and Python-based systems
• Designing and implementing AI-assisted workflows, copilots, or intelligent automation features
• Working with agentic AI patterns (e.g., task orchestration, tool-using agents, workflow automation)
• Applying prompt engineering, evaluation techniques, and guardrails to ensure reliability and compliance
• Collaborating with data and platform teams to operationalize AI-not just prototype it

Deep ML expertise is not required-we're looking for strong engineers who understand how to apply AI capabilities in real products.

Take the first step toward your dream career. Here is what we are looking for in this role.

Qualifications

• 10+ years in web application development, service-oriented architecture, cloud-native platforms, and AI-enabled application design preferred

• 10+ years in full-stack enterprise application development roles, with experience integrating AI, automation, analytics, or data-driven capabilities preferred

• 10+ years leading Software Engineering teams, including mentoring architects and engineers on AI adoption, architectural trade-offs, and modern delivery practices preferred

Professional Skills

• Demonstrate ability to evaluate new technologies, including AI platforms and frameworks, and present comparative analysis of benefits, risks, costs, and implementation considerations

• Strong problem-solving abilities

• Excellent written and verbal communication skills

• Ability to influence technical strategy across product, engineering, security, data, and business stakeholders while advocating for responsible and practical AI adoption

Technical Skills

• Mastery level of software architecture and design, with strong understanding of AI-enabled system design patterns

• Deep understanding of Microsoft .NET and modern application integration patterns for AI-enabled services

• Expert level in relational and non-relational database design, data modeling, and data architecture for analytics and AI use cases

• Experience with enterprise applications in a SaaS Cloud Environment (AWS, Azure, etc.), including scalable deployment patterns for AI, ML, and data-intensive workloads

• Knowledge of AWS products and deployment, with familiarity in cloud AI services, model hosting, automation, monitoring, and secure integration patterns

• Familiarity with AI/ML concepts such as model lifecycle management, prompt engineering, retrieval-augmented generation, evaluation frameworks, observability, and MLOps practices

• Understanding of responsible AI, enterprise data protection, privacy, security, compliance, and governance considerations for production AI systems

AI Use Statement

Employees are expected to appropriately leverage company-approved AI tools to improve productivity and quality while adhering to company policies, protecting confidential information, validating AI-generated content, and exercising sound professional judgment. AI is intended to augment-not replace-professional judgment, critical thinking, accountability, and decision-making. Accountability for all work remains with the employee.

Pay Range

US Pay Ranges

$168,000-$210,000 USD