GEN AI - Architect

Capgemini; Charlotte (NC); Vor Ort; USD 60.000 - 93.000; Vollzeit

Zusammenfassung

Capgemini is seeking an experienced GenAI Architect to lead the design, development, and implementation of enterprise-scale AI solutions on Google Cloud Platform and AWS. You will collaborate with business stakeholders, data scientists, engineers, and product teams to deliver scalable and secure AI systems.

The role focuses on Generative AI, LLMs, RAG, Agentic AI, MLOps, and AI governance, with hands-on architecture using BigQuery, GKE, Vertex AI, Bedrock, SageMaker, and governance frameworks to

Qualifikationen

• Bachelor's or Master's degree in Computer Science, IT, Data Science, AI, or related field.
• Proven experience designing enterprise GenAI solutions at scale.
• Strong knowledge of cloud platforms (GCP/AWS) and governance.

Aufgaben

• Define enterprise GenAI strategy, architecture standards, and roadmaps.
• Design and implement scalable GenAI solutions with foundation models and custom LLMs.
• Architect RAG-based systems integrating structured and unstructured data.
• Develop agentic AI solutions using multi-agent frameworks and orchestration platforms.
• Evaluate foundation models based on business needs, cost, security, and performance.
• Create reference architectures, reusable frameworks, and best practices.
• Architect AI pipelines using BigQuery, Cloud Functions, Dataflow, and GKE.

Kenntnisse

GenAI architecture

Stakeholder comms

Architecture leadership

Governance

Ausbildung

Bachelor's/Master's in CS/IT/Data Science/AI

Tools

GCP

AWS

BigQuery

Dataflow

GKE

Vertex AI

Bedrock

SageMaker

OpenSearch

Terraform

Docker

GitHub Actions

Jenkins

MLflow

LangChain

Semantic Kernel

Kubernetes

Pinecone

Weaviate

Chroma

FAISS

OpenSearch Vector Engine

Jobbeschreibung

We are seeking an experienced GenAI Architect to lead the design, development, and implementation of enterprise-scale Artificial Intelligence solutions leveraging Google Cloud Platform (GCP) and Amazon Web Services (AWS).

The ideal candidate will have expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, cloud-native architectures, MLOps, and AI governance.

This role involves collaborating with business stakeholders, data scientists, engineers, and product teams to deliver scalable, secure, and responsible AI solutions.

Key Responsibilities

• Define enterprise GenAI strategy, architecture standards, and technology roadmaps.


• Design and implement scalable Generative AI solutions using foundation models and custom LLMs.


• Architect RAG-based systems integrating structured and unstructured enterprise data.


• Design Agentic AI solutions leveraging multi-agent frameworks and orchestration platforms.


• Evaluate and select appropriate foundation models based on business requirements, cost, security, and performance.


• Develop reference architectures, reusable frameworks, and best practices for AI adoption.


• Architect AI solutions using:


• BigQuery


• Cloud Functions


• Dataflow


• GKE


• Design AI pipelines utilizing Vertex AI Model Garden and Vector Search.

AWS Responsibilities

• Design AI/ML platforms using:


• Amazon Bedrock


• SageMaker


• AWS Lambda


• Amazon OpenSearch


• ECS/EKS


• Step Functions


• API Gateway


• Implement scalable inferencing, fine-tuning, and model deployment strategies.


• Design and optimize:


• Prompt Engineering frameworks


• Knowledge retrieval systems


• AI Agents and Workflow Automation


• Implement model evaluation frameworks for accuracy, relevance, hallucination detection, and performance monitoring.


• Define guardrails for responsible AI and content moderation.

MLOps & DevOps

• Implement model versioning, monitoring, observability, and governance.


• Design scalable infrastructure using Infrastructure as Code (Terraform/CloudFormation).

Security & Governance

• Ensure AI solutions comply with enterprise security standards.


• Define data privacy, compliance, and responsible AI policies.


• Implement IAM, encryption, audit logging, and model governance frameworks.


• Provide technical leadership to architects, engineers, and data scientists.


• Engage stakeholders to translate business requirements into AI solutions.


• Mentor development teams on GenAI best practices.


• Conduct architecture reviews and technology assessments.

Required Qualifications

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, or related field.

Technical Skills

• Generative AI:
  
  
  
  • Prompt Engineering
  
  
  • RAG
  
  
  • Agentic AI
  
  
  • Semantic Search
  
  
  • Vector Databases
  
  
  
  


• Google Cloud:
  
  
  
  • Gemini
  
  
  • BigQuery
  
  
  • Dataflow
  
  
  • GKE
  
  
  • Pub/Sub
  
  
  
  


• AWS:
  
  
  
  • Amazon Bedrock
  
  
  • SageMaker
  
  
  • OpenSearch
  
  
  • Lambda
  
  
  • ECS/EKS
  
  
  • Step Functions
  
  
  
  


• AI Frameworks:
  
  
  
  • LangChain
  
  
  • LangGraph
  
  
  • CrewAI
  
  
  • AutoGen
  
  
  • Semantic Kernel
  
  
  
  


• Programming Languages:
  
  
  
  • Python
  
  
  • Java
  
  
  • TypeScript
  
  
  • SQL
  
  
  
  


• Vector Databases:
  
  
  
  • Pinecone
  
  
  • Weaviate
  
  
  • Chroma
  
  
  • FAISS
  
  
  • OpenSearch Vector Engine
  
  
  
  


• DevOps & MLOps:
  
  
  
  • Terraform
  
  
  • Docker
  
  
  • GitHub Actions
  
  
  • Jenkins
  
  
  • MLflow
  
  
  
  

Preferred Qualifications

• Experience designing enterprise AI solutions for Financial Services, Healthcare, Insurance, or Retail domains.


• Knowledge of Responsible AI, AI Safety, and Model Governance.


• Experience integrating GenAI solutions with Salesforce, ServiceNow, SAP, or enterprise applications.


• Experience with multimodal AI solutions involving text, image, and document processing.

Certifications (Preferred)

• Google Cloud:
  
  
  
  • Professional Cloud Architect
  
  
  • Professional Machine Learning Engineer
  
  
  
  


• AWS:
  
  
  
  • AWS Certified Solutions Architect – Professional
  
  
  
  


• Additional:
  
  
  
  • Kubernetes Certifications (CKA/CKAD)
  
  
  
  

Desired soft skills

• Strong communication and stakeholder management skills.


• Ability to lead architecture workshops and executive discussions.


• Strategic thinking with strong problem-solving abilities.


• Experience working in Agile and cross-functional environments.

The pay range that the employer in good faith reasonably expects to pay for this position is $43.34/hour - $67.72/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.