Agentic AI Engineer

Capgemini; Nashville, Northern (TN, KY); Hybrid; USD 69,000 - 162,000; Full time

Benefits offered by this job

Paid time off

Medical coverage

401(k)

Job summary

Capgemini is hiring an Onsite Senior Software Engineer to design and implement agentic AI solutions on Google Cloud Platform. The role combines cloud development with AI/ML engineering to deliver scalable architectures for real‑world business challenges in a hybrid US setting.

As part of a scrum team, you will build intelligent agents, manage multi‑agent systems, and secure enterprise integrations using MCP tools. Strong GCP expertise and collaboration skills are essential for success.

Qualifications

• 3–6 years of AI/ML engineering, cloud development, or data engineering with a strong focus on Google Cloud Platform solutions.
• Proven experience developing agentic AI solutions using Vertex AI Agent Builder and Agent Developer Kit (ADK).
• Strong expertise with Vertex AI, including Model Garden, Vertex AI Pipelines, model evaluation, training, tuning, and deployment.
• Advanced knowledge of SQL for BigQuery and Python for machine learning engineering and automation.
• Experience with data preprocessing techniques including scaling, encoding, and imputation.
• Hands‑on experience with Google Cloud Storage, Vertex AI endpoints, and cloud‑native GCP services.
• Experience building and optimizing streaming data pipelines using Dataflow and real‑time inference architectures.
• Knowledge of vector search, retrieval‑augmented generation (RAG), and contextual grounding using BigQuery or AlloyDB vector engines.
• Experience implementing secure enterprise integrations using MCP (Model Context Protocol) and related technologies.
• Familiarity with stateful real‑time processing and emerging agentic architecture innovations.

Responsibilities

• Develop intelligent agents using Vertex AI Agent Builder to automate complex business workflows.
• Leverage the Agent Developer Kit (ADK) to build and manage multi‑agent systems that collaborate to solve end‑to‑end business challenges.
• Implement tools such as MCP (Model Context Protocol) Toolbox to securely connect agents to enterprise databases including BigQuery and Spanner.
• Utilize Vertex AI for model training, tuning, deployment, and lifecycle management.
• Build and optimize streaming data pipelines using Dataflow to enable real‑time inference through RunInference API or Vertex AI endpoints.
• Ground AI models in live business context using vector engines within BigQuery or AlloyDB to improve accuracy and contextual relevance.
• Develop and deploy AI‑powered applications leveraging Google Cloud Platform (GCP) services.
• Work with cloud‑native architectures and integrate applications with GCP‑hosted APIs and services.
• Actively participate in internal and client‑facing meetings, providing regular updates on project milestones and technical blockers.
• Collaborate with business and technology stakeholders to translate high‑level business goals into scalable technical architectures.

Skills

Vertex AI

Agent Builder

ADK

BigQuery

Spanner

Python

BigQuery SQL

Dataflow

Vector search

GCP

Agile

MCP Toolbox

Tools

MCP Toolbox

Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired bya collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Location

This is a hybrid role based in Atlanta GA and Nashville TN.

About the job you’re considering

Capgemini is hiring an Onsite Senior Software Engineer to work with a scrum team in an onshore‑offshore delivery model. The ideal candidate will be responsible for designing and implementing agentic AI solutions on Google Cloud Platform, leveraging Vertex AI, advanced data platforms, and modern AI architectures to solve complex business challenges while collaborating with business and technology teams to deliver high‑quality solutions.

Your Role

• Develop intelligent agents using Vertex AI Agent Builder to automate complex business workflows.
• Leverage the Agent Developer Kit (ADK) to build and manage multi‑agent systems that collaborate to solve end‑to‑end business challenges.
• Implement tools such as MCP (Model Context Protocol) Toolbox to securely connect agents to enterprise databases including BigQuery and Spanner.
• Utilize Vertex AI for model training, tuning, deployment, and lifecycle management.
• Build and optimize streaming data pipelines using Dataflow to enable real‑time inference through RunInference API or Vertex AI endpoints.
• Ground AI models in live business context using vector engines within BigQuery or AlloyDB to improve accuracy and contextual relevance.
• Develop and deploy AI‑powered applications leveraging Google Cloud Platform (GCP) services.
• Work with cloud‑native architectures and integrate applications with GCP‑hosted APIs and services.
• Actively participate in internal and client‑facing meetings, providing regular updates on project milestones and technical blockers.
• Collaborate with business and technology stakeholders to translate high‑level business goals into scalable technical architectures.
• Work in a team covering business and technology with representatives from client to produce overall quality delivery.

Your skills and experience

• 3-6 years of experience in AI/ML engineering, cloud development, or data engineering with a strong focus on Google Cloud Platform solutions.
• Proven experience developing agentic AI solutions using Vertex AI Agent Builder and Agent Developer Kit (ADK).
• Strong expertise with Vertex AI, including Model Garden, Vertex AI Pipelines, model evaluation, training, tuning, and deployment.
• Advanced knowledge of SQL for BigQuery and Python for machine learning engineering and automation.
• Experience with data preprocessing techniques including scaling, encoding, and imputation.
• Hands‑on experience with Google Cloud Storage, Vertex AI endpoints, and cloud‑native GCP services.
• Experience building and optimizing streaming data pipelines using Dataflow and real‑time inference architectures.
• Knowledge of vector search, retrieval‑augmented generation (RAG), and contextual grounding using BigQuery or AlloyDB vector engines.
• Experience implementing secure enterprise integrations using MCP (Model Context Protocol) and related technologies.
• Familiarity with stateful real‑time processing and emerging agentic architecture innovations.
• Strong understanding of cloud infrastructure, scalability, security, monitoring, and performance optimization.
• Experience performing debugging, troubleshooting, and optimization of AI and data platforms.
• Experience working in Agile/Scrum delivery environments.
• Strong analytical thinking and problem‑solving skills.
• Strong communication and collaboration skills with cross‑functional teams.

Compensation

The base compensation range for this role in the posted location is $68,911 to $161,544Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.It is not typical for candidates to be hired at or near the top of the posted compensation range.In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Benefits

Capgemini offers a comprehensive, non‑negotiable benefits package to all regular, full‑time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• Paid time off based on employee grade (A‑F), defined by policy: Vacation: 12‑25 days, depending on grade
• Company paid holidays
• Personal Days
• Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

Equal Opportunity

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this job is traditionally performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.