OverviewResponsibilities- Enterprise SaaS Agentic Architecture (30%)
Define solution architecture patterns for Agentforce and AssistNow implementations, including how agent capabilities are designed, integrated, and governed across enterprise SaaS environments.
- Governance Framework, Engineering Principles & Pattern Library (30%)
Document, maintain, and continuously update engineering principles, governance framework, and reusable patterns to ensure consistent delivery and reduce bespoke implementations across platforms.
- Architecture Review, Approval & Exception Governance (25%)
Work with enterprise platform teams to ensure solution architectures are reviewed and approved per established patterns; govern edge use cases and deviations via controlled, case-by-case review.
- Cross-Platform Alignment & Adoption Enablement (15%)
Enable adoption through clear documentation and guidance so delivery teams can implement solutions consistently across Agentforce and AssistNow, aligned to platform standards and governance expectations.
- Decision-Making Autonomy Moderate - Significant autonomy in the technical aspects of AI model development and implementation, working under the strategic direction provided by the Senior AI Solutions Manager.
- Supervision Required Moderate - Operates with general guidance from the Senior AI Solutions Manager, with regular updates for alignment and support.
- Complexity of Role High - The role requires managing complex AI/ML projects, working with large datasets, and ensuring successful integration with existing systems while maintaining scalability.
- Cross-Functional Interactions Yes - Regular interaction with Data Science, Engineering, IT, digital products and business stakeholders to ensure effective AI solution deployment.
Compensation and Benefits:- The expected compensation range for this position is between $123,500 - $206,750.
- Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
- Bonus based on performance and eligibility target payout is 15% of annual salary paid out annually.
- Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
- In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.
Qualifications- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent practical experience).
- Master's degree (MBA, MIS, MS in CS/Engineering) preferred.
- 12+ years in enterprise architecture / platform engineering / solution architecture, with experience designing and governing enterprise-scale platforms.
- Proven experience architecting AI/agentic solutions in production, including security, governance, auditability, and operability.
Expertise:- Must-have SaaS agentic platform experience:
- Nice to have: Salesforce Agentforce architecture experience including agent/action design, security model, and enterprise integration patterns.
- Nice to have: ServiceNow AssistNow/Now Assist architecture experience including ITSM/Knowledge patterns, ACL/security model, and enterprise integration patterns.
- Enterprise SaaS architecture foundation:
- Strong hands-on architecture experience on Salesforce (Sales/Service Cloud, platform security model, integration patterns).
- Strong hands-on architecture experience on ServiceNow (ITSM/Knowledge/Platform, ACL/security model, integration patterns).
- Proficiency in Python, Java, or C++ (ability to engage engineering teams and design tool/service interfaces).
- Platform architecture for distributed systems, including multi-tenant design and environment isolation (dev/test/prod).
- Strong integration architecture background including API gateway-based patterns, identity integration (SSO/OAuth), and contract-driven interfaces; experience integrating with systems of record such as Salesforce and ServiceNow (SAP integration is a plus).
- Strong operational readiness mindset: defining SLOs, observability standards (logs/metrics/traces), CI/CD gates (testing, security scans, approvals), and production support runbooks.
- Ability to drive adoption through documentation, reference implementations, and enablement of engineers and architects across teams.
- Experience and working knowledge of agentic AI frameworks (e.g., LangChain, CrewAI, MCP, A2A) and deploying AI solutions on AWS/Azure/GCP.
- Strong understanding of designing AI agents (tools/actions, orchestration, memory/state, evaluation) and incorporating advancements in AI/ML responsibly
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