Artificial Intelligence Infrastructure Architect

Accenture India Private Limited; Mumbai; Remote; INR 4,000,000 - 7,000,000; Full time

Job summary

Accenture India Private Limited is seeking an AI Infrastructure Architect to design and build enterprise AI infrastructure, optimize performance, power, and cost across the computational stack.

You will lead design of multi-tenant AI platforms, drive vendor evaluation, and ensure governance, security and compliance while mentoring senior engineers in a remote/hybrid setup.

Qualifications

• 8+ years of engineering experience
• 3+ 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
• Enterprise-grade multi-tenant agentic AI system design experience
• Experience with cost optimization and governance in AI infra

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
• Plan and execute pipelines
• Evaluate and drive adoption of emerging GCP AI capabilities
• Establish engineering standards, design patterns and governance for responsible AI deployment
• Lead cross functional initiatives spanning Platform, Data, ML Research and Product teams
• Partner with executives to translate AI strategy into engineering execution
• Provide technical due diligence for vendor decisions
• Mentor and grow a team of engineers

Skills

Agent Development

Education

15 years full time education

Tools

Vertex AI

GKE Autopilot

AlloyDB

Dataplex

Apigee

Job description

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