GenAI Delivery Architect

Capgemini•Mississauga, ON

2d•CA$76,336 - CA$179,088•Hybrid

About The Position

We are seeking a hands-on GenAI Delivery Architect to design, build, and lead the delivery of enterprise-grade AI Agent solutions. The ideal candidate should have strong experience in Agentic AI, multi-agent architectures, agent orchestration, AI plugins, skills, hooks, MCP servers, tools, enterprise integrations, AI-assisted software development, and cloud-native application delivery. The candidate should be able to rapidly prototype client requirements, validate business use cases through working proofs of concept, and translate business needs into scalable, production-ready AI solutions.

Requirements

Experience designing and implementing GenAI / LLM-based solutions, including agent-based architectures
Strong programming skills in Python; familiarity with TypeScript, Java, or C# is an asset
Hands-on experience with cloud platforms (Azure preferred, AWS or GCP acceptable)
Understanding of modern architecture patterns, including APIs, microservices, and system integrations
Working knowledge of RAG, vector databases, or AI data handling concepts
Experience delivering end-to-end solutions from concept to production
Familiarity with enterprise environments and integration landscapes
Ability to balance innovation with performance, reliability, and governance

Responsibilities

Design and implement multi-agent architectures for enterprise use cases.
Build AI solutions using frameworks such as LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI Agents SDK, Claude Agent SDK, Google ADK, or similar.
Define agent orchestration patterns, memory management, planning, routing, and tool-calling strategies.
Design and develop MCP servers, tools, plugins, skills, hooks, and custom integrations.
Create and maintain Markdown-based specifications, agent instructions, workflows, and prompts to guide AI agents and accelerate solution development.
Build Agent Harnesses for testing, evaluation, observability, and governance of AI agents.
Design, develop, and deploy AI solutions on hyperscaler platforms such as Azure, AWS, and Google Cloud Platform (GCP), leveraging their AI, data, and cloud-native services.
Lead the design and implementation of AI solutions with strong emphasis on Python, along with TypeScript, and some familiarity with Java and C#.
Integrate agents with enterprise systems such as Jira, ServiceNow, Teams, Salesforce, SAP, databases, APIs, and knowledge repositories.
Lead architecture decisions around RAG, vector databases, memory systems, and knowledge graphs.
Establish AI evaluation frameworks, guardrails, monitoring, and production deployment patterns.
Collaborate with business stakeholders and engineering teams to translate business requirements into scalable AI solutions.
Drive end-to-end delivery of GenAI and Agentic AI solutions from concept to production deployment.