AI Architect

Capgemini • New York, NY

7d • $170,000 - $200,000

About The Position

The AI Architecture & Deployment Specialist is a senior, client-facing engineering role responsible for taking AI solutions into production. The role owns architecture, integration, deployment, stabilization, and handover, and is accountable for aligning timelines with stakeholders, explaining technical requirements and gaps, and ensuring solutions work in client environments.

The position scales AI solutions from prototype through build, integration, production deployment, and handover. It defines end-to-end architecture across applications, APIs, data, AI, cloud, security, and enterprise integration, and leads deployment across cloud, hybrid, and on-premise environments in large regulated enterprises. The role also designs multi-agent systems and agent memory architectures, remains hands-on during critical implementation phases, and establishes production deployment, monitoring, resiliency, and support practices.

Success means getting solutions through the final mile into production so they are secure, scalable, observable, supportable, and integrated into the client environment. The posted base compensation range is 170,000–200,000. The role may also be eligible for variable incentives, bonuses, or commissions. Capgemini describes a comprehensive benefits package for regular, full-time employees, with benefits subject to local policy and eligibility.

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 GenAI 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, and 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 ability to work with architecture, security, engineering, and business stakeholders.

Responsibilities

• Own scaling AI solutions from prototype through build, integration, production deployment, and handover.
• Define end-to-end architecture across applications, APIs, data, AI, cloud, security, and enterprise integration.
• Lead deployments across cloud, hybrid, and on-premise 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 patterns, handoffs, state management, and coordination across complex workflows.
• Design agent memory architectures spanning working, episodic, semantic, and long-term memory, with retrieval, retention, and governance patterns.
• Provide hands-on troubleshooting, configuration, performance tuning, and production-readiness support during critical phases.
• 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, and supportable production solutions.
• Align timelines with stakeholders, explain technical requirements and gaps, and ensure solutions work in client environments.

Benefits

• Paid time off, including vacation of 12–25 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 a 401(k) in the U.S. or RRSP in Canada.
• Life and disability insurance.
• Employee assistance programs.
• Other benefits as provided by local policy and eligibility.
• The role may be eligible for variable incentives, bonuses, or commissions, depending on position and applicable laws.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed