AI Infrastructure Architect

Accenture in India; Mumbai; Hybrid; INR 3,000,000 - 5,400,000; Full time

Job summary

Accenture in India seeks an AI Infrastructure Architect to define the long-term technical roadmap for GCP-based agentic AI systems and to design enterprise-scale multi-tenant architectures with complex reasoning and planning.

You will lead cross-functional initiatives across platform engineering, data teams, ML research, and product teams to translate AI strategy into engineering execution.

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.

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 and planning.
• Evaluate and drive adoption of emerging GCP AI capabilities including Gemini and grounding.

Skills

Agent Development

Education

15 years full time education

Tools

Vertex AI

GKE Autopilot

AlloyDB

Dataplex

Apigee

Job description

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