Principal Automation Engineer

What You'll Do

• Role Summary
• Improving operational efficiency, resilience, and process quality by establishing scalable AI automation architecture standards and governance guardrails
• Accelerating transformation delivery and reducing rework through clear design frameworks, decision models, and reusable automation patterns
• Enhancing employee and customer experience by reducing manual work, process fragmentation, and automation risk
• Embedding AI-first architectural practices that improve automation scale, decision quality, and measurable business outcomes

Bar Raiser Expectations

• Holding high standards for architectural clarity, quality, and accountability
• Using data and measurable impact to guide enterprise technical decisions
• Simplifying complex, cross-system and cross-workflow challenges into scalable and sustainable designs
• Guiding AI Automation Engineers, BSAs, and solution designers to raise automation maturity and talent density
• Challenging assumptions respectfully and improving execution rigor across teams
• Leaving every system, process, and architectural framework stronger than it was before

What Your Responsibilities Will Be

• Integration Strategy & Platform Governance
• Leading evaluation of AI automation, agentic workflow, and transformation initiatives across the organization
• Defining architectural decision frameworks and long-term platform strategy for n8n, Boomi, APIs, event-driven orchestration, and AI services to reduce duplication and increase reuse
• Establishing governance guardrails for AI-enabled workflows, agents, prompts, models, data flows, and human-in-the-loop controls to ensure scalability, reliability, auditability, and responsible use
• Anticipating growth, compliance, security, and operational risks across automation platforms and transformation programs before they materialize
• Influencing cross-functional roadmaps with AI Automation Engineers, BSAs, and business leaders based on architectural trade-offs, platform fit, and measurable outcomes

Enterprise Solution Architecture

• Translating enterprise capability needs into clear, implementable technical designs that accelerate AI automation delivery
• Creating architectural blueprints for intelligent workflows, agentic process patterns, and cross-system orchestration that reduce ambiguity and minimize rework
• Designing secure, scalable, and resilient automation patterns across SaaS systems, internal platforms, APIs, data ecosystems, and AI/ML services
• Driving API-first, event-driven, and human-in-the-loop architecture standards that improve interoperability, control, and long-term maintainability
• Leading architecture reviews and representing AI automation and transformation strategy in executive and cross-functional forums

Cross-Functional Technical Collaboration

• Partnering across business, platform, data, security, and engineering functions to create shared clarity from concept through execution for transformation initiatives
• Working closely with AI Automation Engineers and BSAs to turn business process opportunities into governed, implementation-ready automation architectures
• Communicating trade-offs, sequencing, and architectural decisions using data, business impact, risk, and cost considerations
• Solving ambiguous, high-complexity challenges spanning workflows, systems, AI agents, process controls, and enterprise change

Standards, Scalability & Operational Excellence

• Defining enterprise standards, reference architectures, documentation templates, and best practices for AI automation and transformation initiatives
• Establishing performance, reliability, observability, and cost-management benchmarks for deterministic and AI-enabled workflows
• Reducing automation and architectural debt through proactive platform direction, reusable patterns, and rationalization of fragmented solutions
• Improving resilience, scalability, governance, and long-term maintainability across automation platforms and cross-functional process architectures

Mentorship & Organizational Impact

• Providing architectural oversight on high-impact AI automation and business transformation initiatives
• Mentoring AI Automation Engineers, BSAs, and solution designers, raising overall automation architecture maturity and cross-functional execution quality
• Guiding contractor and vendor alignment to enterprise standards for automation, agentic workflows, governance, and platform use
• Elevating organizational AI automation capability through durable architectural principles, reusable patterns, and clear decision frameworks

What You'll Need to be Successful

• AI Expectations
• Strong hands-on experience with modern automation and integration platforms (iPaaS and workflow orchestration tools)
• Experience architecting for platforms such as n8n, Boomi or similar platforms like mulesoft/workato, or comparable automation ecosystems
• Deep understanding of automation patterns, middleware, data transformation, agent orchestration, and human-in-the-loop workflow design
• Strong knowledge of REST, webhooks, OAuth, SSO, API security, and governance best practices for AI-enabled systems
• Experience with cloud-native architectures and AI/ML services (AWS, Azure, or GCP)
• Proven ability to influence enterprise-wide technical direction and partner effectively with AI Automation Engineers, BSAs, and cross-functional leaders