Enterprise Architect

Smarsh

46d•$200,000 - $230,000

About The Position

The Enterprise Architect is a senior technical leadership role accountable for the architectural direction, integrity, and long-term evolution of Smarshâs Conduct platform â a strategic growth engine for the company. This role owns the system-level architecture across services, data, integrations, and platform capabilities, ensuring the platform can scale globally while meeting the rigor of highly regulated environments. This is not a feature-level architecture role. It requires enterprise-level systems thinking, the ability to make consequential architectural decisions, and the judgment to balance near-term delivery with multi-year platform evolution.

Requirements

Enterprise-Level Architectural Ownership
Demonstrated experience defining architecture across business-critical platforms, not just at the service or feature level.
Deep Systems Expertise
Strong command of distributed systems, event-driven architectures, and data-intensive platforms.
Architectural Judgment Under Constraint
Ability to make durable architectural decisions in environments shaped by regulatory requirements, legacy constraints, and delivery timelines.
Transformation Leadership
Experience guiding modernization, re-architecture, or structural evolution across multiple teams.
Technical Authority & Influence
Establishes credibility through depth and clarity of thinking; drives alignment without relying on direct reporting lines.
Platform Mindset
Consistently optimizes for long-term platform health rather than short-term feature delivery
10+ years in senior technical roles, including significant experience as a Principal, Staff, or Lead Architect.
Proven ownership of architectural direction for large-scale, multi-service platforms serving enterprise customers.
Experience designing and evolving distributed, event-driven, or data-intensive systems operating at scale.
Background in regulated or compliance-sensitive environments where auditability and risk management materially influence system design.
Demonstrated success leading cross-team architectural initiatives or platform transformations.
Strong hands-on credibility; able to engage deeply in design, modeling, trade-off analysis, and architectural review.
Experience collaborating across global engineering teams and influencing senior technical stakeholders.
Practical experience integrating AI/ML or LLM-based services into distributed systems.
Understanding of the operational implications of incorporating probabilistic services into deterministic workflows.
Familiarity with service abstraction, API design, and integration patterns that allow AI capabilities to evolve without destabilizing core platform architecture.
Ability to evaluate AI service adoption pragmatically from a scalability, cost, and reliability perspective.

Responsibilities

Own the Architectural Direction of Conduct
Establish and enforce a coherent architectural strategy across the platform. Make and defend high-impact design decisions that shape the system for years to come.
Drive Structural Evolution
Identify and lead architectural changes required to support scale, performance, extensibility, and new capability domains.
Ensure Platform Coherence Across Teams
Define and uphold architectural standards, patterns, and boundaries across multiple engineering teams and services.
Design for Regulatory-Grade Scale
Architect systems that are resilient, auditable, secure, and capable of operating at enterprise data volumes and global customer scale.
Influence Technical Direction Across the Organization
Align Engineering, Product, and customer-facing leadership around architectural trade-offs and long-term platform investments.
Anticipate Downstream Impact
Evaluate how architectural decisions affect performance, cost, operability, compliance posture, and future development velocity.
Architect platform patterns that enable the safe and scalable integration of AI services into Conduct workflows.
Design clean system boundaries and data flows that support the incorporation of external or internally provided AI capabilities.
Ensure AI-enabled components meet performance, reliability, and observability standards within the broader platform.
Improve developer experience by establishing reusable patterns, tooling, and integration standards for AI service consumption.
Partner with centralized AI, data, and governance teams to implement established guardrails within the Conduct architecture.