AI Solution Engineer

About the Company

We are your Energy Technology Partner. We electrify, automate, and digitize every industry, business, and home, driving efficiency and sustainability for all.

At Schneider Electric, our values – IMPACT (Inclusion, Mastery, Purpose, Action, Curiosity, Teamwork) – are the foundation of everything we do. Becoming an Impact Maker means turning sustainability ambitions into actions at the intersection of automation, electrification, and digitization.

Role Overview

As an AI Solution Engineer on the DCR AI Operations team, you will design, build, and deploy AI solutions across two delivery paths: low‑code using platforms such as Microsoft Copilot Studio and Salesforce Agentforce, and pro‑code using Python and modern AI/ML frameworks. You will work closely with business stakeholders, capability Product Owners, Platform architects, Enterprise IT, AI Hub, and the DCR Makers community to turn real problems into production‑ready solutions, owning the full delivery lifecycle.

You will work directly with business stakeholders to turn real problems into production‑ready solutions, owning the full delivery lifecycle from PoC through to go‑live and ensuring every solution is built with the right quality, governance, and documentation standards.

Key Responsibilities

Build and Deliver AI Solutions For DCR Capabilities

• Design and build low‑code AI solutions from PoC to production deployment, using Microsoft Copilot Studio and other low‑code platforms for standard agentic use cases; use Python with modern AI/ML frameworks for more complex use cases.
• Work directly with business stakeholders and digital capabilities to define scope, validate outputs, and iterate based on real user feedback.
• Own the end‑to‑end technical delivery of each use case, from first prototype to go‑live.
• Coordinate with AI Hub and Enterprise IT environment management, following company architecture standards – RAG systems, agentic workflows, multi‑agentic architectures.
• Ensure every solution follows the full validation path – Design, UAT, and Certification Gateways – before going live.

Embed Quality and Documentation Into Every Build

• Document each solution thoroughly – architecture decisions, connector configuration, prompt design, known limitations – so it can be operated, maintained, and evolved with confidence.
• Build solutions that are designed to scale and be reused across capabilities where possible.
• Contribute to DCR's library of templates, reusable components, and prompt patterns.

Contribute to the DCR Low‑Code Makers Community

• Share what you learn – tricks, shortcuts, patterns that work – with the growing community of makers across DCR capabilities.
• Help shape DCR's low‑code standards, best practices, and governance guidelines as the model matures.

Stay Sharp on the Platform

• Keep your Microsoft Copilot Studio certification current and expand your knowledge across the broader AI ecosystem: LLM providers, agentic frameworks, low‑code platforms.
• Evaluate new pre‑built agents, connectors, and capabilities as they become available across platforms.
• Bring platform insights back to DCR AI Operations to continuously improve how we deliver.

Key Skills

Must have

• Hands‑on experience building solutions with one or more low‑code AI platforms – Microsoft Copilot Studio, Salesforce Agentforce, Power Automate.
• Hands‑on experience with Python and LLM APIs – Azure OpenAI, OpenAI, Anthropic or equivalent, including prompt engineering at code level.
• Understanding of AI evaluation and guardrails – measuring output quality, detecting hallucinations, applying content filtering and responsible AI patterns.
• Strong understanding of conversational AI concepts: agent design, intent handling, knowledge base management, escalation flows.
• Ability to work directly with business stakeholders – translate a business problem into a working solution without needing a fully detailed specification.
• Comfortable managing multiple use cases simultaneously, with different stakeholders and business contexts.
• Fluent in English – written and spoken.

Good to have

• Microsoft Copilot Studio or Power Platform certification.
• Experience with enterprise data connectors – SharePoint, Dynamics 365, SAP, Salesforce.
• LangGraph agentic framework, LLMOps/MLOps exposure via LangSmith.
• Data engineering fundamentals – SQL, basic pipeline work (Databricks or Fabric), enough to prepare data for AI consumption.
• Background in a commercial or customer‑facing function – Sales, Customer Support, Services – to understand the problems you are solving.

Who You Are

• You pick the right tool, not the favorite one. Some problems are a C