Senior AI Systems Architect & Delivery Lead

Ernst & Young Oman

San Antonio (TX)

Hybrid

USD 144,000 - 329,000

Full time

14 days+

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Job summary

EY seeks a senior Distinguished Engineer to lead AI-native system delivery in regulated sectors such as tax and finance. The role blends architecture enforcement with real-world delivery, working across Forward Deployed Engineers and cross‑cell teams to ensure safe, auditable production deployments.

The ideal candidate combines deep technical judgment, client presence, and ability to translate field realities into durable enterprise patterns.

Qualifications

10+ years of experience delivering complex AI enterprise systems
Deep experience with distributed systems, cloud platforms, and integration-heavy architectures
Hands-on experience with modern AI-enabled application stacks (e.g., agentic systems, orchestration frameworks, LLM-backed services)
Proven ability to operate in forward-deployed or customer-facing engineering roles
Track record of creating reusable technical patterns or platforms
Experience collaborating with architecture, product, and platform teams
Strong understanding of software delivery lifecycle, quality gates, and production readiness in enterprise settings
Bachelor’s or Master’s degree in Computer Science or related field
Expertise with AI/ML lifecycle management, observability, and validation approaches
Experience with AI governance, security, and cost controls in production environments
Ability to influence client and internal stakeholders through technical credibility
Experience building reference implementations, test harnesses, and validation frameworks
Exposure to regulated delivery contexts (e.g., financial services, tax, healthcare, risk platforms)

Responsibilities

Serve as a cross-engagement technical authority, ensuring delivery implementations adhere to architecture intent, safety, and economic constraints in regulated environments.
Synthesize learnings into durable reference integrations, validated implementations, and reusable patterns that reduce repeated failure modes.
Work with AI agents to support regulated safe-to-ship decisions by contributing technical evidence and validation inputs.
Operate as a player‑coach, contributing directly to complex system design and implementation while guiding delivery teams toward repeatable approaches.
Own the consolidation, prioritization, and communication of cross‑cell product signals, converting field observations into evidence-based recommendations.
Partner with Product Engineering and Product Architecture to package consolidated client patterns into business cases and platform investments.
Participate in shaping sessions, architecture reviews, and prioritization discussions, advocating changes to improve portability and customer outcomes.