AI Enablement Engineer

The AI Enablement Engineer will help build, deploy, and support production AI tools, agents, and workflows used across Revalize. Working closely with business stakeholders and senior engineers, they help translate business needs into secure, reliable, and scalable solutions that integrate with enterprise platforms such as Salesforce and Microsoft 365. The role contributes across the full solution lifecycle - from scoping and development through launch, monitoring, user support, documentation, and continuous improvement - with guidance from more experienced team members. The ideal candidate is building strong software engineering and applied AI skills, brings a practical mindset, and communicates clearly with both technical and non-technical stakeholders. 

Responsibilities
 

• Help build and ship AI-powered tools and agents: tool and API integrations, agent workflows, backend services, and lightweight user-facing interfaces 
• Help operate what you ship: monitor system health, help investigate incidents, and support internal users - with guidance from senior engineers 
• Contribute to integrations between AI systems and enterprise platforms such as CRM (e.g. Salesforce) and Microsoft 365, working within established auth and permission models 
• Help develop LLM pipelines: retrieval, structured data extraction, scoring logic, prompt and tool design, and validation of outputs before they touch business systems 
• Use AI coding tools as a core working method, reviewing and governing their output to production quality 
• Follow security-first practices: least-privilege access, service accounts, and audit logging 
• Work with business stakeholders to understand requests and help turn ambiguous asks into shippable tools 
• Help internal users adopt AI tooling: answer questions, run short enablement sessions, and evaluate new tools as they emerge 
• Write documentation as you build - runbooks and decision notes that let others operate what you made 

• 1+ years building software (internships, academic, or professional projects count), with some exposure to LLM/generative AI features beyond simple prototypes 
• Working Python skills; familiarity with REST APIs and some exposure to a modern frontend framework (e.g. React with TypeScript) 
• 1+ years of experience with AWS and/or Azure (related certifications a plus) 
• Experience in LLM tool-calling or agent frameworks, and workflow/automation platforms (e.g. n8n, Power Automate, or similar) 
• Understanding of LLM fundamentals: RAG, embeddings, structured extraction, prompt design, and judgment about when outputs need human review 
• Eager to make progress in ambiguous situations and asks good questions rather than waiting for complete specs 
• Communicates clearly with non-technical colleagues; writes documentation others can actually use 
   

Nice to have

• Experience with MCP servers, the Anthropic/Claude ecosystem, or enterprise AI platform administration 
• Exposure to predictive ML (scoring, classification) or evaluation design for AI systems 
• Salesforce API and data-model experience; Microsoft Graph or Entra ID experience 
• Manufacturing, CPQ/PLM, or B2B vertical SaaS domain exposure 
• Experience supporting or training end users on technical tools