AI Enablement Engineer

Revalize

. Help build and ship AI-powered tools and agents, including tool and API integrations, agent workflows, backend services, and lightweight user-facing interfaces .

Posted 9/21/2026full-timeRemote • United StatesJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building AI-powered tools and integrations, with strong skills in Python, REST APIs, and LLM fundamentals. Capable of translating business needs into technical solutions while ensuring effective communication and documentation.

Highest-signal resume keywords

Python ProgrammingLLM FundamentalsREST API IntegrationAWS/Azure ExperienceFrontend Framework Exposure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingLLM Tool-CallingREST API IntegrationWorkflow AutomationStructured Data ExtractionPrompt DesignData ValidationIncident InvestigationDocumentation WritingUser Support

Soft Skills

Clear CommunicationProblem-SolvingAdaptabilityCollaboration

Tools & Technologies

SalesforceMicrosoft 365N8nPower AutomateMCP ServersAnthropic/Claude EcosystemMicrosoft GraphEntra ID

Certifications & Qualifications

AWS CertificationAzure Certification

Industry Keywords

B2B SaaSManufacturingCPQPLM

Tech Stack

Tools & technologies

AWSAzurePythonReactTypeScript

About the role

Key responsibilities & impact

Help build and ship AI-powered tools and agents, including tool and API integrations, agent workflows, backend services, and lightweight user-facing interfaces
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 Salesforce and Microsoft 365
Help develop LLM pipelines for retrieval, structured data extraction, scoring logic, prompt and tool design, and output validation
Use AI coding tools, reviewing and governing their output to production quality
Apply least-privilege access, service accounts, and audit logging
Work with business stakeholders to translate ambiguous requests into shippable tools
Help internal users adopt AI tooling by answering questions, running short enablement sessions, and evaluating new tools
Write documentation, runbooks, and decision notes
Contribute across the solution lifecycle from scoping and development through launch, monitoring, user support, documentation, and continuous improvement

Requirements

What you’ll need

1+ years building software; internships, academic, or professional projects count
Some exposure to LLM/generative AI features beyond simple prototypes
Working Python skills
Familiarity with REST APIs
Some exposure to a modern frontend framework, such as React with TypeScript
1+ years of experience with AWS and/or Azure
Experience in LLM tool-calling or agent frameworks
Experience with workflow/automation platforms, such as n8n or Power Automate
Understanding of LLM fundamentals including RAG, embeddings, structured extraction, prompt design, and judgment about when outputs need human review
Ability to make progress in ambiguous situations and ask good questions
Clear communication with non-technical colleagues
Ability to write usable documentation
Related AWS/Azure certifications are a plus
Experience with MCP servers, the Anthropic/Claude ecosystem, or enterprise AI platform administration is nice to have
Exposure to predictive ML or evaluation design for AI systems is nice to have
Salesforce API and data-model experience is nice to have
Microsoft Graph or Entra ID experience is nice to have
Manufacturing, CPQ/PLM, or B2B vertical SaaS domain exposure is nice to have
Experience supporting or training end users on technical tools is nice to have

Benefits

Comp & perks

PTO
Sick Leave
Parental Leave
Medical Insurance
Dental Insurance
Vision Insurance
401(k) Plan
Health Savings Account
Life Insurance
Employee Assistance Program
Bonus eligible position