AI Infrastructure Architect

Project Role : AI Infrastructure Architect
Project Role Description : Architect and build custom Artificial Intelligence (AI) infrastructure/hardware solutions. Optimize AI infrastructure/hardware performance, power consumption, cost and scalability of computational stack. Advise on AI infrastructure technology and vendor evaluation, selection and full stack integration.
Must have skills : Agent Development
Good to have skills : NA
Minimum 12 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Lead GCP Agentic AI Engineer
Level Principal or Staff
Experience 8 or more Years
Work Mode Remote or Hybrid
Employment Full Time
Key Responsibilities
Define and own the long term technical roadmap for GCP based agentic AI systems across the organization
Design enterprise scale multi tenant multi agent architectures supporting
Complex reasoning
Planning
Execution pipelines
Evaluate and drive adoption of emerging GCP AI capabilities including
Gemini
Grounding
Agent to Agent protocols
Open source frameworks
Establish engineering standards design patterns and governance frameworks for responsible AI deployment covering
Safety
Bias
Auditability
Lead cross functional technical initiatives spanning
Platform engineering
Data teams
ML research
Product teams
Partner with executive stakeholders to translate AI strategy into engineering execution
Provide technical due diligence for
Key vendor decisions
Build or buy decisions
Mentor and grow a team of senior and mid level engineers
Required Skills And Qualifications
8 or more years of engineering experience
3 or more years leading complex AI ML or agentic platform initiatives
Expert level GCP knowledge across the full stack including
Vertex AI
GKE Autopilot
AlloyDB
Dataplex
Apigee
Emerging GCP AI infrastructure
Deep mastery of agentic system design including
Hierarchical agent orchestration
Dynamic tool calling
Persistent memory
Multi modal reasoning
Human in the loop governance
Strong expertise in
LLM fine tuning
Model evaluation at scale using Vertex AI Pipelines
Demonstrated ability to design for enterprise requirements including
Multi tenancy
Data residency
Zero trust security
Regulatory compliance
Experience with cost optimization at scale including
Spot and preemptible GPU workloads
Resource quotas
FinOps on GCP
Exceptional communication skills with the ability to translate deep technical complexity for
Executive audiences
Customer audiences
Engineering audiences
Proven track record of
Delivering platform level impact
Driving organizational engineering culture

Work arrangement
No