AWS Solution Architect

Role Description

Capgemini is hiring an AWS Solutions Architect - Agentic AI & Amazon Bedrock to work with a scrum team in an onshore-offshore delivery model.

• Own the AWS solution design for an Enterprise Agentic AI build and act as the primary technical face to the client.
• Lead architecture discussions and client alignment while staying hands-on enough to shape prompts, agent configuration, and evaluation approaches.
• Accountable for the end-to-end AWS AI solution architecture for a multi-agent solution leveraging Amazon Bedrock, RAG, guardrails, human-in-the-loop approval workflows, and governed writes to enterprise systems of record.
• Assess the client’s existing AWS and AI landscape; confirm reuse versus net-new capabilities and establish scope, assumptions, and dependencies early.
• Lead client workshops and drive alignment across platform, security, architecture, and data-owner teams.
• Present solution design, architecture recommendations, project progress, and technical decisions to stakeholders and leadership teams.
• Define agent evaluation methodologies, acceptance criteria, and delivery sequencing across Agile sprints.
• Stay selectively hands-on with prompt engineering, Bedrock agent configuration, and evaluation framework setup.
• Capable of conceptualizing latest technology landscape requirements and driving technical solutions.
• Work in a team covering business and technology with representatives from client to produce overall quality delivery.

Qualifications

• 10+ years of solid experience in AWS Solution Architecture with extensive client-facing enterprise consulting experience.
• Hands-on experience with Amazon Bedrock, Agentic AI architectures, Retrieval Augmented Generation (RAG), and Vector Search technologies.
• Experience working in Agile projects.
• Strong understanding of various AWS, AI, and enterprise technology components and their capabilities.
• Strong workshop facilitation skills with the ability to effectively engage client architects, engineering leaders, and business stakeholders.
• Strong analytical thinking to assess enterprise requirements and connect systems, data sources, and AI capabilities in an efficient manner.
• Excellent problem-solving skills to resolve complex technical challenges and provide effective solutions and troubleshooting.
• Strong knowledge of activities across every phase of delivery from requirement analysis to product release and post-production support.
• Hands-on experience and expertise with Amazon Bedrock, Agentic AI solutions, multi-agent architectures, prompt engineering, and evaluation frameworks.
• Experience designing and implementing enterprise AI solutions using RAG, Vector Databases, Guardrails, and Human-in-the-Loop approval mechanisms.
• Experience assessing existing AWS environments and determining reuse opportunities versus net-new implementations.
• Knowledge of AWS services including IAM, Lambda, API Gateway, S3, CloudWatch, and cloud-native integration patterns.
• Experience with enterprise system integrations such as ServiceNow, ITSM platforms, and systems of record.
• Familiarity with AI security and governance including IAM, PII protection, auditability, and compliance requirements.
• Familiarity with Bedrock AgentCore and Model Context Protocol (MCP).
• Experience defining evaluation frameworks, acceptance criteria, and quality metrics for Generative AI and Agentic AI solutions.

Requirements

• The base compensation range for this role in the posted location is $98,497 to $233,248.
• Compensation may be subject to change as permitted by law.
• The actual compensation offered may fall outside of the posted range and will be determined based on multiple factors.
• In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions.

Benefits

• 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.