Job Summary
We are seeking an experienced AI Workflow Engineer to identify, design, implement, and scale AI-enabled workflows across business functions. This role will partner with leaders across Finance/RevOps, Go-To-Market, Services, HR/Legal, and Engineering to embed AI into real operating workflows and drive measurable business outcomes. The ideal candidate combines software engineering experience, AI fluency, business and technology consulting, workflow automation, stakeholder management, and change management expertise.

Key Responsibilities
• Partner with leaders across Finance/RevOps, Go-To-Market, Services, HR/Legal, and Engineering to identify high-impact opportunities to embed AI into operational workflows.
• Facilitate discovery sessions to map current-state processes, quantify pain points, define desired outcomes, and translate ambiguous business needs into clear workflow requirements and success metrics.
• Build and maintain an AI workflow roadmap based on business impact, readiness, and organizational change capacity.
• Align AI workflow priorities with function leaders and the AI Transformation team.
• Conduct build-versus-buy assessments for SaaS tools, platforms, and automation solutions and provide clear recommendations and implementation approaches.
• Lead change management and enablement initiatives, including working sessions, playbooks, training sessions, brown bags, and team coaching.
• Create reusable patterns and standards for AI-enabled internal tools, including workflow templates, governance checklists, and measurement frameworks.
• Establish operational guardrails for AI-enabled workflows in partnership with Security, Legal, and Compliance teams.
• Address data handling, PII protection, access controls, prompt injection resilience, and human-in-the-loop requirements.
• Define evaluation and monitoring standards covering accuracy, quality, safety, cost, latency, and adoption.
• Implement feedback loops to continuously improve AI-enabled workflows.
• Collaborate with technical teams to define requirements, delivery plans, and implementation strategies for AI workflow solutions.
• Measure and communicate business outcomes to distinguish meaningful impact from adoption activity.

Required Qualifications
• 6+ years of experience in internal consulting, business operations, business systems, product operations, solutions architecture, or an equivalent business and technology role.
• 4+ years of software engineering experience shipping internal AI-native tools to production.
• Experience establishing an internal AI program, workflow automation Center of Excellence (COE), or AI-for-employees capability.
• Experience in B2B SaaS, enterprise workflows, and/or regulated or high-compliance environments involving privacy, security, and auditability.
• Strong stakeholder management skills, with the ability to influence senior leaders, align cross-functional teams, and drive decisions amid competing priorities.
• Ability to translate business problems into structured requirements, operating metrics, and phased delivery plans.
• Understanding of LLM-based systems, including prompting, retrieval, and tool use/function calling at a conceptual level.
• Ability to evaluate AI solution quality, risk, cost, and latency trade-offs.
• Experience evaluating and implementing software solutions, including build-versus-buy assessments, vendor evaluation, security reviews, rollout planning, and ongoing ownership models.
• Comfort working with technical teams and artifacts such as PRDs/briefs, user stories, acceptance criteria, and basic data models.
• Ability to prototype solutions using low-code/no-code tools.
• Strong analytical and measurement skills, including the ability to establish baselines, instrument outcomes, and report measurable impact.
• Excellent written and verbal communication skills, with the ability to create concise briefs, facilitate effective workshops, and communicate trade-offs to technical and non-technical audiences.
• High ownership and bias toward action, with the ability to thrive in fast-moving SaaS environments and evolving AI ecosystems.
• Bachelor's degree in Business, Information Systems, Engineering, Computer Science, or a related field, or equivalent practical experience.