Sr. AI Integration Engineer

Light Edge Solutions is developing the IT solutions that will propel businesses forward over the next 10 years. Using a combination of shared and private/dedicated platforms, Light Edge has been successful in offering businesses alternatives that streamline operations, improve reliability and reduce costs.

If you are passionate about creating real solutions that help businesses with cutting‑edge technology, want to be challenged to think out of the box and be in a position where you can impact change on a daily basis, then Light Edge can offer you a dynamic corporate environment built on teamwork and personal responsibility.

The Senior AI Integration Engineer plays a central role in building, integrating, deploying, and supporting AI‑driven workflows across Lightedge’s core operational and business systems. This position is an execution partner to AI architecture leadership, helping translate agentic design concepts and approved business needs into production‑ready AI agents, automations, and integrations that improve workflow execution, operational efficiency, and decision support.

The ideal candidate combines strong software engineering and systems integration skills with practical experience delivering AI‑enabled workflows in business environments. This person must be comfortable working directly with stakeholders to gather requirements, refine scope, and iterate quickly, while also owning a backlog of business‑facing AI workflows and serving as the primary technical owner for those workflows once they move into production.

• AI Agent, Harness & Workflow Development:
  Design, develop, and maintain production‑grade AI agents, harnesses, workflows, services, and integrations that support internal business processes and cross‑functional execution.
• AI Agent & Workflow Lifecycle Management:
  Own the end‑to‑end lifecycle of AI agents and AI‑driven workflows, from intake and requirements shaping through production readiness, deployment, monitoring, support, periodic review, and continuous improvement.
• Stakeholder Partnership:
  Work directly with internal teams to gather requirements, refine scope, collect feedback, and translate business needs into practical AI‑enabled workflow solutions.
• Owned Backlog:
  Maintain and execute a backlog of high‑value business‑facing AI workflows and automations that align with Lightedge priorities across operations, support, sales, and other internal functions.
• System Integration:
  Build and support integrations across enterprise systems such as Service Now, Salesforce, portals, APIs, middleware, and other workflow platforms used by the business.
• Production Ownership:
  Serve as the primary technical owner for AI workflows once they move from prototype into production, unless and until a deliberate transition to another long‑term owner is defined.
• Operational Support:
  Provide first‑level support for production AI workflows that support critical business processes, including monitoring, issue triage, defect resolution, incident coordination, and early‑life stabilization.
• Controls and Readiness:
  Implement the controls required for safe production adoption, including testing, evaluation, observability, secrets handling, approval steps, rollback planning, and change‑management alignment.
• Engineering Standards:
  Contribute to codebases, deployment pipelines, support practices, and implementation standards for AI‑enabled workflow delivery.
• Optimization:
  Monitor, evaluate, and optimize the accuracy, reliability, cost, and business effectiveness of deployed AI workflows and integrations.
• Documentation:
  Maintain clear technical documentation, workflow diagrams, runbooks, support notes, and production‑readiness artifacts for delivered solutions.
• Cross‑Functional
  
  Collaboration:
  
  Partner with AI architecture, Security, Compliance, IT, Operations, and platform teams to ensure AI workflows are secure, supportable, and aligned with governance requirements.
• Communications:
  Regularly communicate delivery status, risks, support needs, and business impact to stakeholders and leadership.
• Architecture Contribution:
  Contribute implementation insight and field feedback into broader AI design…