AI Solutions Architect

• Serve as an architect specializing in agent based artificial intelligence solutions, designing robust frameworks and data infrastructure that enable secure and scalable AI agent lifecycle management for enterprise environments while aligning with governance standards and hybrid work models to deliver impactful outcomes for business stakeholders and society at large.

Responsibilities

• Design comprehensive AI agent lifecycle architectures that define how agents are created, orchestrated, monitored, and retired to ensure reliability, traceability, and sustainable performance across enterprise platforms.
• Develop scalable AI agent frameworks that enable modular components, reusable patterns, and interoperable services so that complex agent ecosystems can evolve efficiently and remain maintainable over time.
• Guide AI agent engineering practices by defining reference architectures, coding conventions, and integration standards that help engineering teams deliver robust agent behaviours with predictable outcomes and minimal technical debt.
• Create AI agent data infrastructure designs that specify data flows, storage models, access controls, and observability mechanisms to ensure agents operate on high-quality data while meeting security and compliance expectations.
• Establish agentic AI governance models that include policies, approvals, risk controls, audit mechanisms, and accountability structures to support responsible AI adoption and reduce unintended societal and business impacts.
• Collaborate actively in a hybrid work model with cross functional teams to translate complex business challenges into agent driven solutions that enhance customer experiences and operational efficiency.
• Align AI agent architectures with ethical principles, regulatory requirements, and organizational values to ensure agent decisions and interactions remain transparent, fair, and trustworthy for end users and communities.
• Coordinate with platform, data, and security teams during day shifts to integrate agent capabilities into existing technology landscapes while minimizing disruption and ensuring operational stability.
• Provide architectural guidance on observability and incident response for AI agents so that anomalies can be detected quickly, investigated effectively, and remediated with minimal impact on services.
• Standardize design patterns for agentic AI that encourage reuse, reduce complexity, and accelerate delivery of new capabilities without compromising quality or governance controls. -Document architecture decisions, design rationales, and technical blueprints in clear English so that stakeholders can understand agent solutions and make informed decisions on investments and priorities.
• Evaluate emerging agentic AI tools and frameworks, conduct fit for purpose assessments, and propose adoption roadmaps that position the organization at the forefront of responsible AI innovation.
• Mentor engineering and data teams on agent design concepts, lifecycle practices, and governance principles to build shared understanding and strengthen organizational capability in advanced AI. -Qualifications
• Demonstrate deep experience designing and configuring AI agent lifecycles including creation, orchestration, monitoring, and retirement within complex enterprise environments.
• Exhibit strong hands-on background in AI agent frameworks and engineering practices including building modular agents, defining interaction protocols, and integrating with data and platform services.
• Show proven expertise in AI agent data infrastructure design across ingestion, storage, transformation, and access layers with an emphasis on data quality, resilience, and security.
• Apply practical knowledge of agentic AI governance including policy design, risk assessment, compliance alignment, and audit readiness for production AI systems.
• Display familiarity with hybrid work collaboration tools and practices, enabling effective communication, documentation, and joint design sessions for distributed technical teams.
• Demonstrate proficiency in English reading writing and speaking to communicate complex architectural concepts clearly with technical and nontechnical stakeholders.
• Combine at least ten years of experience in AI, data, or software architecture roles with exposure to agent-based systems to handle intricate design decisions and long term technology roadmaps