AI Infrastructure Architect

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