Agentic AI Engineer
About the role
Location
About the job you're considering
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.
#LI-SD1
The base compensation range for this role in the posted location is $68,911 to $161,544
Capgemini 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.
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
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Who can apply
The employer didn't state any visa, work authorization, citizenship or clearance requirements in this posting. Confirm with the employer before applying.
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