7 days ago
Base Salary
$170k - $200k/yr
Responsibilities
- Own scaling AI solutions from prototype through build, integration, production deployment, stabilization, and handover.
- Define end-to-end architecture across applications, APIs, data, AI, cloud, security, and enterprise integration.
- Lead deployment across cloud, hybrid, and on-premises environments in large regulated enterprises.
- Integrate AI platforms with enterprise systems, data sources, identity, security, and operational tooling.
- Design and implement multi-agent systems, including agent roles, orchestration, handoffs, state management, and tool integration.
- Design agent memory architectures covering working, episodic, semantic, and long-term memory with retrieval, retention, and governance patterns.
- Perform hands-on troubleshooting, configuration, performance tuning, and production-readiness work.
- Establish deployment patterns using containers, Kubernetes, CI/CD, Infrastructure as Code, and DevSecOps practices.
- Define monitoring, logging, observability, resiliency, rollback, runbooks, and support requirements.
- Turn successful prototypes into scalable, secure, supportable production solutions.
Requirements
- Architect-level experience as a Solution Architect, Enterprise Architect, Principal Engineer, or equivalent.
- Proven ownership of enterprise solutions from architecture through production deployment and operationalization.
- Production deployment experience with at least one leading AI platform, such as OpenAI, Anthropic Claude, or Google Gemini.
- Hands-on experience designing and building enterprise generative AI and multi-agent systems, including orchestration, handoffs, state management, and tool integration.
- Strong experience with agent memory architectures, including working, episodic, semantic, and long-term memory, with appropriate retrieval and governance patterns.
- Strong understanding of APIs, microservices, distributed systems, event-driven architecture, and enterprise integration.
- Hands-on familiarity with Docker, Kubernetes, CI/CD, DevSecOps, and Infrastructure as Code.
- Experience deploying AI evaluation metrics, guardrails, and AI observability across enterprise environments.
- Banking or insurance delivery experience and the ability to work with architecture, security, engineering, and business stakeholders.
Benefits
- Paid time off, including 12–25 vacation days depending on employee grade, company-paid holidays, personal days, and sick leave.
- Medical, dental, and vision coverage, or provincial healthcare coordination in Canada.
- Retirement savings plans such as 401(k) in the U.S. and RRSP in Canada.
- Life and disability insurance.
- Employee assistance programs and other benefits based on local policy and eligibility.
- Regular, full-time employees receive a comprehensive benefits package.
Tech Stack
Categories
Solutions Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.