About the Team & Role
We are seeking a high-impact Solution Engineer to join the Enterprise Applications Architecture team. This role is dedicated to accelerating our business by weaving AI and hyperautomation directly into our core enterprise platform ecosystem. Rather than building from scratch, you will focus on unlocking native AI features within our existing vendors, augmenting gaps through targeted engineering, and integrating with our centralized AI Platform to drive operational excellence.
How you'll make an impact
Strategic Governance & Standardization: Collaborate with cross-functional steering committees to establish enterprise-wide AI standards, reference architectures, and ethical guardrails, ensuring a unified and scalable approach to autonomous agent deployment.
Strategic Integration: Influence the roadmap of our Enterprise Application portfolio (CRM, ERP, HCM, etc.) to ensure we are maximizing out-of-the-box AI capabilities.
Architecture & Augmentation: Design and implement "bridging" solutions where native platform features fall short, leveraging our internal AI Platform to ensure a unified intelligence layer.
Hyperautomation Leadership: Lead the design and deployment of digital employees and AI agents, integrating them with RPA and machine learning to create a seamless, hybrid workforce that automates complex, end-to-end business functions.
Hands-on Execution: Lead AI initiatives from rapid Proof of Concept (POC) to production-ready systems, ensuring solutions are scalable, secure, and maintainable.
Efficiency First: Uphold the "don't reinvent the wheel" philosophy by prioritizing the reuse of existing frameworks and centralized AI infrastructure.
Cross-Functional Liaison: Serve as the technical authority between the AI Platform team and the business-facing application teams to ensure technical alignment and data integrity.
Technical Leadership: Mentor engineering staff on AI best practices, contribute to resource planning, and act as a senior escalation point for complex integration challenges.
Market Intelligence: Maintain a pulse on the "Big Tech" enterprise AI landscape to advise leadership on when to "buy vs. configure vs. build."
Experience you'll bring
Education: BS/BA degree in Computer Science, Information Systems, or a related technical field.
Experience: 8+ years in Software/Systems Engineering with a heavy focus on Enterprise Applications.
AI/ML Expertise: 4+ years of hands-on experience implementing AI/ML solutions, specifically involving Large Language Models (LLMs), NLP, or Predictive Analytics within a corporate environment.
Integration Mastery: Proven ability to design complex system integrations using APIs, middleware, and event-driven architectures (e.g., Kafka).
Stakeholder Management: Demonstrated experience navigating high-level business requirements and translating them into technical specifications for diverse IT and business audiences.
Preferred Qualifications
Platform Specifics: Deep experience with major enterprise ecosystems (e.g., Salesforce, Workday).
AI Governance: Familiarity with AI ethics, data privacy (GDPR/CCPA), and the "Human-in-the-loop" design patterns.
Hyperautomation Proficiency: Experience with hyperautomation tools and frameworks (e.g., UiPath) to drive business efficiency.
Agile/DevOps: Experience leading development pods using Agile methodologies and implementing MLOps/DevOps pipelines for continuous delivery.
Product Mindset: Ability to leverage User Experience (UX) principles to ensure AI features actually improve productivity rather than adding friction.
