GenAI Ops Solution Architect

About the role

The Solution Architect will lead the design, governance, and evolution of enterprise scale Generative AI platforms and solutions. This role is critical in establishing architecture standards, platform capabilities, integration patterns, governance controls, and engineering practices that enable secure, scalable, and reusable GenAI adoption across the enterprise.

Responsibilities

• Define and govern the enterprise GenAI platform architecture.
• Establish architecture standards, design patterns, and reusable frameworks for enterprise AI adoption.
• Lead solution design for RAG, Document Intelligence, Agentic AI, Evaluation, Observability, and Governance capabilities.
• Drive the design and implementation of centralized GenAIOps capabilities including: RAG & Retrieval Services AgentOps ModelOps / LLMOps Evaluation Pipelines Observability & Monitoring AI Governance & Controls.
• Define reference architectures and integration patterns for onboarding GenAI use cases.
• Cloud & Integration Strategy
• Define cloud architecture and deployment strategies across Azure, AWS, or hybrid environments.
• Establish enterprise integration patterns for APIs, data platforms, document repositories, workflow systems, and identity providers.
• Lead architecture decisions around scalability, resiliency, security, and performance.
• Engineering Leadership
• Provide technical leadership to Value Engineers, Context Engineers, Alignment Engineers, and ModelOps teams.
• Support platform onboarding and use case architecture activities.
• Mentor engineering teams and drive adoption of best practices.
• Evaluate emerging GenAI technologies and recommend platform enhancements.
• Stakeholder Engagement
• Collaborate with business and technology leaders to align architecture decisions with strategic objectives.
• Support roadmap planning, platform evolution, and capability expansion initiatives.
• Act as the primary architecture authority for enterprise GenAI initiatives.

Requirements

• 10+ years of experience in solution architecture, enterprise architecture, cloud architecture, or platform engineering.
• 3+ years of experience designing and implementing Generative AI and enterprise AI solutions.
• Deep understanding of: Large Language Models (LLMs) Retrieval Augmented Generation (RAG) Agentic AI Prompt Engineering AI Evaluation Frameworks ModelOps / LLMOps AI Governance.
• Experience designing enterprise scale cloud solutions on Azure, AWS, or GCP.
• Strong knowledge of microservices, APIs, event driven architectures, and distributed systems.
• Experience leading architecture governance and enterprise technology standards.
• Strong stakeholder management and executive communication skills.
• Experience in establishing a scalable and reusable enterprise GenAI platform.
• Experience accelerating onboarding of GenAI use cases through reusable architecture patterns.
• Experience ensuring alignment with governance, security, and compliance requirements.
• Experience improving platform adoption, operational efficiency, and engineering productivity.
• Experience enabling sustainable long term ownership through architecture standardization and knowledge transfer.

Qualifications

• To be successful in this role, candidates should have:
• 10+ years of experience in solution architecture, enterprise architecture, cloud architecture, or platform engineering.
• 3+ years of experience designing and implementing Generative AI and enterprise AI solutions.
• A deep understanding of Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic AI, Prompt Engineering, AI Evaluation Frameworks, ModelOps / LLMOps, and AI Governance.
• Experience designing enterprise scale cloud solutions on Azure, AWS, or GCP.
• A strong knowledge of microservices, APIs, event driven architectures, and distributed systems.
• Experience leading architecture governance and enterprise technology standards.
• Strong stakeholder management and executive communication skills.
• Experience in establishing a scalable and reusable enterprise GenAI platform.
• Experience accelerating onboarding of GenAI use cases through reusable architecture patterns.
• Experience ensuring alignment with governance, security, and compliance requirements.
• Experience improving platform adoption, operational efficiency, and engineering productivity.
• Experience enabling sustainable long term ownership through architecture standardization and knowledge transfer.

Skills

• Leadership and stakeholder engagement skills.
• Technical proficiency in Generative AI, cloud architecture, and enterprise platform engineering.
• Ability to define and implement architecture standards and governance controls.
• Experience with large-scale system design and implementation.
• Knowledge of Generative AI technologies such as LLMs, RAG, and ModelOps.
• Experience with cloud platforms like Azure, AWS, or GCP.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Benefits

CGI offers competitive compensation, comprehensive insurance options, matching contributions through the 401(k) plan and the share purchase plan, paid time off for vacation, holidays, and sick time, paid parental leave, learning opportunities and tuition assistance, wellness and well-being programs, and more.

Pay

CGI offers a reasonable estimate of the compensation range for this role, which is $113,400.00 - $198,400.00 in the U.S.

Schedule

This position is performed onsite five days a week at our client site in Strongsville, OH, Dallas, TX, or Pittsburgh, PA.