AI Architect

Quick Facts

• Role: AI Architect

Description

Set the technical direction for designing, evaluating, integrating, and operating AI systems that improve critical human workflows. Define reference architectures and evaluation practices, guide cross-functional teams, and prototype or validate key patterns to ensure quality, reliability, safety, and value. Partner with product and engineering to turn high-value opportunities into measurable systems running in production.

Responsibilities

• Define AI architecture direction, including reference architectures, design principles, and trade-offs across quality, autonomy, reliability, latency, cost, and complexity.

• Build an evaluation discipline: success measures, representative datasets, evaluation methods, regression checks, and quality thresholds.

• Shape production readiness practices such as tracing/observability, versioning, monitoring, incident response, privacy, security, and lifecycle management.

• Enable teams to ship with reusable patterns, reference implementations, architecture reviews, and prototype-to-production guidance.

• Connect architecture to outcomes by partnering with product, operations, and domain teams to measure improvements.

• Stay close to implementation by prototyping high-risk/foundational designs and reviewing critical implementations.

• Track the evolving ecosystem by evaluating models, agent runtimes, orchestration approaches, and evaluation tooling and recommending adoption.

Requirements

• 8+ years of backend software development experience.

• 3+ years of AI architecture experience with demonstrated organization-wide impact.

• Experience designing and delivering production software systems with substantial AI/ML work.

• Evidence-based track record setting technical direction across teams.

• Practical understanding of LLM applications, including retrieval and context construction, tool use, agent patterns, model selection, and failure handling.

• Experience defining quality expectations and building evaluations for AI behavior tied to production outcomes.

• Judgment on when AI is appropriate vs deterministic workflows.

• Production experience covering observability, privacy and security, reliability, cost, latency, and safe human escalation.

• Clear communication across engineering, product, and executive audiences; comfort prototyping and reviewing implementations.

Benefits

• Pay range: $129,600–$288,000 USD (final offer depends on factors such as location, experience, market demands, and internal parity).