Software Architect

Vertex Inc.•Remote - PA, PA

About The Position

Serve as a technical authority within the Commercial AI Center of Excellence (CAI CoE), leading AI-as-a-Service (AIaaS) enablement at enterprise scale. Design, build, and evolve shared AI services, agentic frameworks, and paved-road patterns that enable product and engineering teams to deliver AI-powered capabilities safely and consistently. Establish reference architectures, technical standards, and patterns for agentic orchestration, tool calling, and structured outputs across production-grade AI systems. Lead complex, cross-team technical initiatives spanning multiple value streams; review and influence AI designs across product teams to ensure alignment with enterprise standards. Optimize performance, cost, and scalability of AI workloads while partnering with Security, Cloud Platform, and SRE teams to meet reliability and compliance requirements. Operate at enterprise scale, influencing architecture, standards, and long-term technical direction across PDD while remaining hands-on with critical AI infrastructure and services.

Requirements

15+ years of experience in AI/ML software engineering, with demonstrated impact at Senior Principal or equivalent level.
Deep expertise in distributed systems and cloud-native architectures.
Strong understanding of classical AI, GenAI, agentic systems, retrieval architectures, evaluation, and monitoring.
Hands-on experience building LLM systems and RAG pipelines in production.
Expertise with cloud platforms, with Azure strongly preferred.
Strong system design skills, including APIs and developer platforms.
Experience building reusable SDKs, MCPs, and multi-agent orchestrations.
Proven ability to influence technical decisions across teams without direct authority.
Experience operating in regulated SaaS environments.

Nice To Haves

Bachelor's degree in Computer Science, Engineering, or a related discipline; advanced degree preferred.
Industry experience in tax or other regulated domains (insurance, fintech, or healthcare).
Experience with vector databases and retrieval optimization.
FinOps for GenAI: experience modeling and optimizing LLM token and inference costs.
Data science or classical AI background (beyond prompt engineering).
Strong executive communication and technical storytelling skills.
Equivalent combination of education, training, and relevant professional experience accepted in lieu of a formal degree.

Responsibilities

Design, build, and evolve shared AI services, agentic frameworks, and paved-road patterns.
Establish reference architectures, technical standards, and patterns for agentic orchestration, tool calling, and structured outputs.
Lead complex, cross-team technical initiatives spanning multiple value streams.
Review and influence AI designs across product teams to ensure alignment with enterprise standards.
Optimize performance, cost, and scalability of AI workloads.
Partner with Security, Cloud Platform, and SRE teams to meet reliability and compliance requirements.
Influence architecture, standards, and long-term technical direction across PDD.
Remain hands-on with critical AI infrastructure and services.