Enterprise AI Architect (Strong AWS & Iac)

Job Role: Principal/Enterprise AI Architect

Location: Jersey City, NJ (Onsite)

Eligibility: US Citizens/ GC holders only

Mode of Interview: Onsite/Face-To-Face

Role purpose

• Set the architecture, engineering standards, platform strategy, and technical governance for enterprise AI and GenAI capabilities. This role guides senior engineering teams and ensures AIRP is scalable, reusable, observable, cost-efficient, secure, and compliant, while remaining AWS-first today and cloud-agnostic by design.
• Client-specific emphasis
• Own the cloud-agnostic AI blueprint while leveraging AWS as the current implementation platform.
• Define reusable Terraform/IaC and DevOps pipeline patterns that can be federated across multiple AIRP use cases.
• Ensure architecture supports AI for business, AI for engineering, and responsible citizen development without fragmenting controls.

Primary ownership

• Target-state enterprise AI architecture, AIRP reference patterns, reusable platform capabilities, and guardrails.
• LLMOps, AI gateways, model-serving strategy, evaluation platforms, observability, governance, and operating standards.
• Technical assurance for high-risk or high-impact AI initiatives across banking use cases.

Key responsibilities

• Define target-state architecture for AIRP, LLM platforms, model hubs, AI gateways, RAG services, agent frameworks, orchestration layers, and model-serving infrastructure.
• Establish enterprise standards for AI SDLC, LLMOps, MLOps, evaluation, release management, operational resilience, and production support.
• Create AWS implementation patterns that align with a cloud-agnostic blueprint and minimize unnecessary vendor lock-in.
• Define standards for Terraform modules, reusable IaC templates, environment strategy, pipeline promotion, approvals, observability, secrets, rollback, and operational controls.
• Guide architecture for secure, scalable, and cost-efficient inference across cloud, hybrid, private, and containerized environments.
• Define guardrail patterns for hallucination mitigation, bias monitoring, harmful-content controls, prompt injection defense, data leakage prevention, and human oversight.
• Lead design reviews for critical AI systems and provide technical assurance to architecture, risk, security, and governance forums.
• Partner with cybersecurity, risk, compliance, legal, audit, product, business, and citizen-development enablement teams.
• Assess emerging AI technologies and recommend adoption based on business value, maturity, risk, cost, portability, and regulatory fit.

Must-have candidate profile

• 10+ years in AI/ML systems, distributed systems, enterprise architecture, or platform engineering.
• Deep experience with LLMs, RAG, embeddings, model serving, AI orchestration, evaluation frameworks, and AI infrastructure.
• Proven track record defining architecture and technical standards across multiple engineering teams.
• Strong AWS cloud architecture experience or comparable hyperscaler depth, with clear ability to design cloud-agnostic AI platform patterns.
• Experience shaping Terraform/IaC standards, DevOps pipelines, secure deployment patterns, observability, resiliency, and platform operating models.
• Ability to influence senior stakeholders and operate across business, technology, risk, compliance, security, data, and architecture forums.

Preferred experience

• Global bank, fintech, financial-services, or regulated-enterprise platform experience.
• Experience with enterprise AI platforms, private LLM deployments, internal model hubs, AI gateways, multi-cloud AI strategy, or platform blueprint ownership.
• Familiarity with Responsible AI, model risk management, audit expectations, technology risk controls, and citizen development governance.