Principal Software Architect

Role overview Set the technical direction for enterprise software capabilities that use AI, translating product and business needs into secure, scalable designs. You will work across engineering, product, data, security, and business teams to shape architecture, help operationalize AI features, and coach teams on sound engineering and responsible AI practices.

Responsibilities - Assess AI, machine learning, cloud, and architecture technologies, comparing their benefits, risks, costs, and suitability for product needs. - Review system designs and data flows for scalability, performance, security, and readiness for AI capabilities. - Define and document reference architectures for AI services, including data ingestion, retrieval-augmented generation, inference, monitoring, and human review. - Guide integration of language models and AI services into .NET- and Python-based systems, including automation and agent-based workflows. - Establish practical approaches to prompts, evaluations, guardrails, model lifecycle management, and production observability. - Promote privacy, security, explainability, bias mitigation, governance, and appropriate use of enterprise data. - Mentor engineers and architects, and guide appropriate use of AI-assisted engineering tools.

Requirements - Extensive experience in software architecture and design, including enterprise web applications, service-oriented systems, and cloud-native platforms. - Deep knowledge of Microsoft .NET and application integration patterns for AI-enabled services. - Strong expertise in relational and non-relational databases, data modeling, and data architecture for analytics or AI. - Experience with enterprise cloud applications and scalable deployments for data-intensive workloads; AWS experience is specifically sought. - Ability to evaluate emerging technologies and communicate trade-offs clearly to technical and business stakeholders. - Strong problem-solving, written communication, and verbal communication skills. - Background leading software engineering teams and mentoring others through architectural decisions and modern delivery practices.

Nice to have - Familiarity with prompt engineering, retrieval-augmented generation, evaluation frameworks, MLOps, and AI observability. Deep machine learning expertise is not required. - Experience integrating AI, automation, analytics, or other data-driven capabilities into enterprise products.

Benefits and work setup - The listing gives a U.S. pay range of $168,000–$210,000.