Agentic AI Delivery Specialist

Accenture

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
San Francisco, CAMilwaukeeDallasColumbusKirklandCincinnatiNew YorkClevelandOklahoma CityAustinChicagoSt. PeteHartfordPittsburghSt. LouisMiamiSacramentoRaleighMinneapolisMountain ViewScottsdaleMorristownBostonDenverPhiladelphiaDes MoinesOverland ParkLos AngelesCharlotteWalnut CreekCarmelSeattleHoustonArlingtonAtlantaRedmondBentonvilleBeavertonNashvilleDetroitSan Diego
Salary
$70,350–$196,000 / yr
Employment
Full-time
Posted
28 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $207k
This role $133k
$49k $267k
below market most similar roles pay here above market

This role pays less than 93% of similar roles. Most pay $167,715–$246,150 — the blue band above. At the midpoint, this role pays about $133k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Accenture

Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.

Accenture currently has 174 open roles on FindRole.

Listed pay typically runs $94,400–$266,300 across 128 roles with salary data.

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At a glance

TL;DR · Agentic AI Delivery Specialist

JOB TITLE: Google Agentic AI Delivery Specialist The Google Agentic AI Delivery Specialist joins the Accenture Google Business Group to serve as a product-minded engineer. This role involves designing, building, and demonstrating innovative agentic-first solutions on Google Cloud Platform to help clients transition from legacy mindsets to modern, value-driven software products. You will participate in technical discovery workshops, develop proof-of-concept solutions, and provide technical expertise to global delivery teams. Key responsibilities include architecting multi-agent workflows and managing continuous delivery sprints. Required skills include hands-on experience with Vertex AI, Gemini, BigQuery, Terraform, and CI/CD practices. You must possess deep knowledge of agentic components like reasoning engines, planning, tool use, and Retrieval-Augmented Generation. The role solves the business problem of moving clients toward Product-Led Operating Models using advanced Google Cloud technologies.

What you'll do

  • Translate client business requirements into GCP technology design elements during technical discovery workshops.
  • Design, build, test, and deploy innovative agentic-first solutions on Google Cloud Platform.
  • Develop and present compelling proof-of-concept solutions using Vertex AI, Gemini, BigQuery, and Terraform.
  • Act as a subject matter expert to guide delivery teams on Product Agile Operating Models and sprint structures.
  • Architect and build agentic workflows including reasoning engines, planning, tool use, and Retrieval-Augmented Generation (RAG).
  • Implement software engineering best practices such as CI/CD, automated testing, and secure product building.
  • Provide technical expertise to global delivery teams to customize Google Cloud Agentic solutions for clients.

What we're looking for

  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent (minimum 12 years) work experience.
  • Minimum of 6 years work experience is required if the candidate holds an Associate’s Degree.
  • Minimum of 3 years of experience in a hands-on, client-facing technology role such as a Google Cloud Engineer or Technology Consultant.
  • Minimum of 3 years of deep, hands-on experience architecting and building solutions on GCP.
  • Minimum of 2 years of experience interacting with project team members distributed across the globe.
  • Minimum of 2 years of proven experience on Google Cloud technologies OR 1 year of implementation experience on Agentic systems or Google Gemini Enterprise Partner Specialist certifications.
  • Google Cloud Professional certifications and experience with Vertex AI, BigQuery, and Terraform are preferred.

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