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# AI Engineer

- **Company:** Scigon Solutions
- **Location:** Chicago, IL, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $108,160.0 - $145,600.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Distributed Systems, Identity and Access Management, Role-Based Access Control, Search Technologies, Software Engineering, Systems Integration, Flexi (Photoshop Plugin), Google Cloud, Enterprise Software Applications, Large Language Models, Multi-Agent Systems, Prompt Engineering, AI Platforms, Kubernetes, Api Design, Software Version Control
- **Published:** September 24, 2026
- **Apply:** https://www.dice.com/job-detail/547b636f-5fb2-4315-9251-6877934ad179

## About the Role

The ideal candidate combines hands-on experience with modern LLM platforms, strong software engineering fundamentals, and the ability to work directly with business partners to translate ideas into production-ready solutions., * Proven experience developing, publishing, and managing Claude Skills or plug-ins in a production environment.

 * Demonstrated success deploying AI capabilities that are actively used by business stakeholders.
 * Ability to contribute immediately with minimal onboarding and ramp-up time.

Enterprise Delivery Experience

 * Experience building and deploying technology solutions within regulated or highly governed enterprise environments.
 * Strong understanding of security controls, compliance requirements, access management, and operational governance.
 * Comfortable working within structured delivery processes and change-control frameworks.

Business Partnership Skills

 * Strong communication and stakeholder management abilities.
 * Capable of translating business challenges into practical AI-enabled solutions.
 * Experience collaborating with both technical and non-technical audiences., * 5+ years of experience in software engineering, automation engineering, or a related technical discipline.
 * At least 2 years of experience designing and deploying production-grade solutions powered by large language models.
 * Strong proficiency in Python development and API-based integrations.
 * Experience with enterprise software integration patterns and distributed systems.
 * Solid engineering practices, including testing, source control, observability, monitoring, and supportability.
 * Hands-on experience with modern LLM ecosystems, including prompt engineering, model configuration, tool integration, and function execution.
 * Experience working within public cloud environments such as Azure, Google Cloud Platform, Vertex AI, or equivalent technologies.
 * Ability to evaluate AI use cases pragmatically and determine when traditional engineering approaches may be more effective.
 * Self-directed and capable of independently leading technical initiatives in a fast-moving environment., * Experience building AI agents and multi-agent workflows.
 * Familiarity with orchestration platforms and agent frameworks.
 * Understanding of Model Context Protocol (MCP) implementations and agent-to-agent integrations.
 * Experience with RAG architectures, vector databases, embeddings, and semantic search solutions.
 * Knowledge of modern identity and access management concepts, including RBAC, service accounts, agent identities, and least-privilege models.
 * Previous experience supporting organizations operating within highly regulated industries such as insurance, financial services, healthcare, or similar sectors.

## Description

We are seeking an Applied AI Engineer to help design, deploy, and operationalize enterprise AI capabilities. This individual will play a key role in enabling AI-powered solutions through native platform functionality, delivering practical business outcomes, and ensuring compliance with enterprise governance and security standards., * Design, deploy, and manage reusable AI capabilities within enterprise AI platforms, including skills, tools, and plug-in functionality.

 * Drive the complete lifecycle of AI enablement solutions, from intake and configuration through deployment, governance, ongoing support, and optimization.
 * Configure foundation models such as Claude, Gemini, and similar technologies to support enterprise automation and business workflows.
 * Deliver AI solutions from concept through production implementation, ensuring scalability, security, and operational readiness.
 * Integrate existing enterprise systems, services, and approved tools using available connectivity frameworks and protocols.
 * Collaborate with Security, Cloud, and Infrastructure teams to implement appropriate access controls, identity management practices, and credential governance.
 * Ensure solutions comply with established AI governance standards, including auditability, monitoring, risk controls, and operational guardrails.
 * Partner with engineering, automation, data, and business teams to identify opportunities and deliver impactful AI-driven capabilities.