Lightedge

Sr. AI Integration Engineer

Des Moines, Iowa · Senior

Sponsorship not specifiedDetected 55 days ago

JavaScriptTypeScriptPythonJavaC#Distributed SystemsFull-Stack DevelopmentSQLVector DatabasesAWSAzureCloud PlatformsKubernetesCI/CDLLMsRAGAgentic AIIncident ResponseComplianceSalesforceHIPAALeadershipCommunicationCollaboration

About the role

Using a combination of shared and private/dedicated platforms, LightEdge has been successful in offering businesses alternatives that streamline operations, improve reliability and reduce costs.
The ideal candidate combines strong software engineering and systems integration skills with practical experience delivering AI-enabled workflows in business environments.
With over 20 years in business, LightEdge offers a full stack of best-in-class IT services delivering flexibility, security, and control.

Responsibilities

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.
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 ServiceNow, Salesforce, portals, APIs, middleware, and other workflow platforms used by the business.
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.
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.

Requirements

Experience taking prototypes, proofs of concept, or citizen-developed automations into governed production environments with appropriate controls, reliability, and supportability.
Experience supporting production applications, integrations, or automations with direct operational ownership responsibilities.
Working knowledge of security, access controls, logging, monitoring, and change-management practices for business-critical systems.
Strong proficiency in Python for AI integrations, workflow automation, and data processing.
Experience with one or more of JavaScript/TypeScript, Java, or C# for API and application development.
Experience translating business requirements into production-ready technical workflows and integrations.
Experience evaluating AI outputs, prompt behavior, workflow quality, and operational reliability before production release.
Experience deploying and supporting production systems in cloud environments such as AWS, Azure, or GCP.
Ability to work directly with stakeholders to gather requirements, define scope, and iterate based on feedback.
Excellent communication skills and ability to translate technical decisions into business impact.

Nice to have

Experience integrating AI-enabled workflows into ServiceNow, Salesforce, or similar enterprise platforms.
Experience with prompt engineering, evaluation, and tuning of generative AI systems in production contexts.
Experience with Kubernetes and container-based deployment models.
Experience with MCP-style integration patterns, orchestration layers, or agent-accessible tool frameworks.
Experience with SQL and working with operational or analytics data across enterprise platforms.
Familiarity with vector databases, RAG pipelines, and workflow patterns that combine structured system context with LLM reasoning.
Experience with enterprise LLM platforms including ChatGPT, Claude, Gemini, Copilot, or similar tools.
Previous experience owning a backlog of automation or AI workflow enhancements for internal business users.

Compensation

LightEdge annually undergoes third-party audits for ISO 20000-1, ISO 27001, HIPAA, PCI-DSS 3.2, and SSAE 18 SOC 1 Type II, SOC 2 Type II and SOC 3.

Visa & Work Authorization

Experience taking prototypes, proofs of concept, or citizen-developed automations into governed production environments with appropriate controls, reliability, and supportability

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This listing is sourced directly from Lightedge's careers page and normalized into a canonical job model.