Lead Software Engineer (Skills - Gen AI, LLM, Python, Lean Six Sigma)

Role summary

The Lead AI Process Transformation Engineer leads larger, complex and cross-functional workflow redesign and AI-enabled transformation opportunities. The role is the senior process-and-AI engineering anchor for OEE, combining enterprise process transformation, capability and maturity assessment, portfolio leadership, practical solution architecture, hands-on technical credibility, executive influence and coaching.

Role purpose and scope

This role operates within OEEs process-first transformation model. It owns the path from ambiguous enterprise problem to validated current state, redesigned workflow, bounded AI-enabled solution, governance approval, adoption and realized value. The role leads the second AI Process Engineer, supports the AI Builders Network and works across business and technology teams to ensure that technical choices follow process evidence rather than lead it.

Enterprise workflow transformation leadership

• Lead complex, cross-functional workflow discovery across people, process, technology, data, policies, controls, systems and organizational boundaries.
• Frame ambiguous business challenges into clear outcomes, process boundaries, operating assumptions, measures and decision requirements.
• Guide current-state and future-state design using process maps, SIPOCs, value-stream views, service blueprints, decision flows and operating-model views.
• Challenge solution-first requests and ensure the sequence Eliminate, Simplify, Standardize, Integrate, then Automate or apply AI is followed.
• Define process ownership, roles, decision rights, controls, exception paths, escalation routes, service expectations and management routines.
• Review and assure the quality of transformation charters, process designs, value cases, implementation plans and control approaches.

Capability mapping and transformation portfolio leadership

• Lead capability-mapping and maturity-assessment activities linking enterprise outcomes to capabilities, workflows, owners, KPIs, systems, data and dependencies.
• Build and govern a prioritized pipeline of workflow redesign and AI-enabled transformation opportunities.
• Assess opportunities using strategic alignment, customer impact, volume, effort, cycle time, quality, risk, controls, data readiness, feasibility, reuse and value potential.
• Establish decision gates for discovery, redesign, prototype, pilot, production handoff, scale, remediation and retirement.
• Manage dependencies, risks, decisions and capacity across multiple transformation opportunities and technical partners.
• Provide concise executive views of portfolio health, value, risks, readiness and decisions required.

AI solution architecture and technical direction

• Translate redesigned workflows into AI-enabled solution strategies covering tasks, inputs, outputs, context, knowledge, integrations, controls, human review and operational ownership.
• Define solution patterns for agentic workflows, AI assistants, retrieval-based solutions, workflow automation and deterministic controls.
• Lead or co-lead proofs of concept and bounded implementations using enterprise-approved platforms such as Microsoft Copilot Studio, Power Automate, Azure AI capabilities, approved APIs and Python.
• Provide technical direction on prompt engineering, grounding, retrieval-augmented generation, orchestration, evaluation and integration patterns.
• Determine when bounded low-code or coded implementation is appropriate and when production engineering, architecture or data-platform support is required.
• Assure that solution design includes human-in-the-loop decisions, exception handling, fallback, access controls, auditability, supportability and lifecycle ownership.

AI Builders Network and team leadership

• Act as the senior process-transformation partner for Principal AI Leads, AI Builders and business leaders on complex or cross-functional opportunities.
• Coach the second AI Process Engineer and builders on workflow discovery, process-first solutioning, value measurement, agent design, testing and adoption.
• Establish reusable playbooks, templates, prompts, test packs, control patterns and solution assets for enterprise reuse.
• Conduct design reviews and provide escalation support where process, technology, risk or ownership choices are unclear.
• Build practical process-transformation and AI fluency across OEE and participating business teams.

**Value realization, governance and ado…