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RoleFocus
You will lead the technical architecture and delivery of enterprise-grade AI platforms. Your mission is to move clients from "Experimentation" to "Production" by architecting high-performance, secure, and cost-optimized environments for Gemini models.You willbe responsibleforarchitectingand implementingGoogle cloud, Gemini Enterprise, VertexAIand other Googlespecific technology focused solutions for Accenture’s clients.
Key Responsibilities & Toolset Proficiency
Generative AI & Model Management
Gemini 1.5 Pro/Flash & Model Garden:Deploy and fine-tune Gemini models for specialized tasks (reasoning, long-context analysis, multimodal processing).
Vertex AI Studio:Manage the lifecycle of prompts and model versions, ensuringoptimalperformance across different enterprise use cases.
Orchestration & Agentic Logic
Vertex AI Agent Builder:Build "System-of-Action" agents using the native Google stack to minimize latency and maximize security.
Multi-Agent Systems:Architect complex, stateful agentic workflows,utilizingGoogle’ssolutions and other relevant industry leading solutionsto solve complex business use-cases spanning multiple industries.
Agent Development Kit (ADK):Standardize the creation of agents to ensure portability and consistency across the enterprise.
Data & Vector Infrastructure
BigQuery(Vector Search):Integrate structured business data with unstructured vector embeddings directly withinBigQueryto power grounded, real-time AI responses.
Vertex AI Search & Conversation:Implement RAG (Retrieval-Augmented Generation) at scale, ensuring agents have access to the most recent and relevant enterprise knowledge.
Cloud Architecture & Engineering
Microservices (Cloud Run/GKE):Containerize and scale agentic applications using GKE for high-performance workloads or Cloud Run for serverless efficiency.
Event-Driven Design (Pub/Sub):Build asynchronous, resilient AI pipelines that trigger actions across the enterprise based on real-time data events.
Development &MLOps
Python & API Design:Craft robust, clean, and performant Python code and design secure APIs that connect Gemini to legacy systems (ServiceNow, SAP, Oracle).
CI/CD for ML (MLOps):Implement automated testing, deployment, and monitoring pipelines to manage model drift and ensure reliability.
Productivity Tools:LeverageGemini Code Assist,Gemini CLI, andAntigravityto accelerate thedevelopmentlifecycle and automate repetitive infrastructure tasks.
Technical Requirements
Platform Mastery:Advanced experience with theVertex AIsuite, including Model Garden and Agent Builder.Experience with Gemini CLI, Code Assist, Agent developmentkitand the future breadth of Google development tools.
Engineering Excellence:Proventrack recordofdesigning and deployingAI and Agentic frameworks, architecting agentic workflowscompliant with responsible AIguideline. Sound knowledge of Google cloud solutions including Google Kubernetes engine and other relevant tools.
MLOpsDiscipline:Hands-on experience withVertex AI Pipelinesor Kubeflow for managingproductionAI lifecycles.
Data Savvy:ProficiencyinSQL/BigQueryand vector database management.
Security Mindset:Deep understanding of Google CloudVPC Service Controls, IAM,RAIand enterprise security protocols for AI.
Qualifications
5+ years incloudengineering,Machinelearningand AI development.
3+ years specifically focused on AI/ML implementationand deploying agentic systems
Proventrack recordof delivering end-to-endAIsolutionsforenterprise clients.
Qualifications
Why this role?
In this role, youaren'tjust an "AI developer"—you are aReinvention Engineer. You are building the "Enterprise AIfoundation” for our clients across business verticals.You will be the technical lead who ensures thatwhen our clientsdeploymulti-agent systems, the infrastructure is as robust, secure, and performant as their core banking or ERP systems.
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