AI Architect
US$80,000 – US$160,000 / yr base salary
Posted 21 Aug 2026
Advertised as “GCP AI Architect”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- People management
| Base salary | US$80,000 – US$160,000 / yr |
|---|
Field of studyComputational Linguistics, Computer Science, Mathematics, Artificial Intelligence, Machine learning, Natural Language Processing (or related)
Study levelBachelor's or higher
We currently have a career opportunity for an Technical Architect to join our team located in New York.
Job Overview:
We are seeking a distinguished technical leader to architect the next generation of our platform on Google Cloud (GCP). You will not just select services; you will design fault-tolerant, planetary-scale distributed systems that integrate state-of-the-art AI into the core of our engineering culture. You will bridge the gap between "Research" and "Production," applying SRE rigor to AI lifecycles.
The Technical Architect provides technology direction, ensures project implementation compliance, and utilizes technology research to innovate, integrate, and manage technology solutions. As a Technology Architect, you will significantly contribute to identifying best-fit architectural solutions for one or more projects; you will collaborate with some of the best talent in the industry to create and implement innovative high quality solutions, participate in Sales and various pursuits focused on our clients' business needs. This role is considered part of the Business Unit Leadership team and may mentor Junior Architects and /or development team members.
Perficient is always looking for the best and brightest talent and we need you! We’re a quickly-growing, global digital consulting leader, and we’re transforming the world’s largest enterprises and biggest brands. You’ll work with the latest technologies, expand your skills, and become a part of our global community of talented, diverse, and knowledgeable colleagues.
Responsibilities
- Architecting for "Google-Scale" & Reliability
- Design highly resilient, cloud-native architectures rooted in SRE principles. You will define the strategy for GKE (Kubernetes) multi-cluster orchestration, service mesh (Istio/Anthos) connectivity, and global load balancing. You will enforce strict SLOs and Error Budgets at the architectural level to ensure high availability (99.99%+) while managing the trade-offs between consistency (Spanner) and availability.
Productionizing Vertex AI & Large Models
- Design highly resilient, cloud-native architectures rooted in SRE principles. You will define the strategy for GKE (Kubernetes) multi-cluster orchestration, service mesh (Istio/Anthos) connectivity, and global load balancing. You will enforce strict SLOs and Error Budgets at the architectural level to ensure high availability (99.99%+) while managing the trade-offs between consistency (Spanner) and availability.
- Orchestrate the end-to-end MLOps lifecycle leveraging the Vertex AI ecosystem.
- You will architect pipelines that move models from notebooks to production seamlessly, managing feature stores (Vertex Feature Store) and model serving endpoints. You will lead the integration of Gemini/PaLM models, defining patterns for RAG (Retrieval-Augmented Generation) using Vector Search and BigQuery to deliver low-latency, context-aware AI.
- Implementing "Responsible AI" & Safety Guardrails
- Operationalize AI Safety and Governance. You will architect rigorous evaluation frameworks to detect model drift, hallucination, and bias before deployment. You are responsible for implementing input/output guardrails and ensuring data sovereignty within GCP, treating model governance with the same rigor as IAM security policies.