AI Enablement Engineer

Location: Hybrid, Reston, Virginia, United States. Standard working hours for U.S.-based employees are 8:00 am to 5:00 pm Eastern Time.

Company

hirify.global develops manufacturing technology, including CPQ, PLM, and design solutions, serving more than 16,000 global customers.

What you will do

• Build and ship AI-powered tools, agents, API and tool integrations, backend services, and lightweight user interfaces.
• Monitor production system health, investigate incidents, support internal users, and contribute to continuous improvement.
• Integrate AI systems with enterprise platforms such as Salesforce and Microsoft 365 using established authentication and permission models.
• Develop LLM pipelines covering retrieval, structured data extraction, scoring logic, prompt and tool design, and output validation before business-system use.
• Use AI coding tools while reviewing and governing their output to production quality; follow least-privilege, service-account, and audit-logging practices.
• Work with stakeholders to turn ambiguous requests into shippable tools, support adoption through questions and enablement sessions, evaluate emerging tools, and create runbooks and decision notes.

Requirements

• At least 1 year of software-building experience, including internships, academic projects, or professional projects, plus exposure to LLM or generative AI features beyond simple prototypes.
• Working Python skills, familiarity with REST APIs, and some exposure to a modern frontend framework such as React with TypeScript.
• At least 1 year of experience with AWS and/or Azure.
• Experience with LLM tool-calling or agent frameworks and workflow or automation platforms such as n8n or Power Automate.
• Understanding of LLM fundamentals, including RAG, embeddings, structured extraction, prompt design, and deciding when outputs require human review.
• Ability to make progress in ambiguous situations, ask effective questions, and communicate clearly with non-technical colleagues.
• Ability to write documentation that others can use.

Nice to have

• Experience with MCP servers, the Anthropic/Claude ecosystem, or enterprise AI platform administration.
• Exposure to predictive ML, including scoring and classification, or AI-system evaluation design.
• Salesforce API and data-model experience, or Microsoft Graph and Entra ID experience.
• Exposure to manufacturing, CPQ/PLM, or B2B vertical SaaS.
• Experience supporting or training end users on technical tools.
• Related AWS or Azure certifications.

Culture & Benefits

• AI-forward approach focused on using technology to improve manufacturing outcomes.
• Full-time, bonus-eligible employment with PTO, sick leave, and parental leave.
• Medical, dental, and vision insurance; 401(k) plan; health savings account; life insurance; and employee assistance program.
• Work is organized around collaboration with business stakeholders, senior engineers, and internal users.

Hiring process

• Qualified applicants complete a 30-minute online pre-employment assessment.