AI Engineer

SCIGON is seeking an Applied AI Engineer to design, deploy, and operationalize enterprise AI capabilities. The position centers on implementing LLM-powered solutions with governance, security, and integration into existing systems, with an emphasis on production readiness and ongoing support.

Role Responsibilities

• Design, deploy, and manage reusable AI capabilities within enterprise AI platforms, including skills, tools, and plug-in functionality.
• Own the full lifecycle of AI enablement solutions, from intake and configuration through deployment, governance, ongoing support, and optimization.
• Configure foundation models such as Claude, Gemini, and comparable technologies to enable 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 access controls, identity management practices, and credential governance.
• Ensure compliance with AI governance standards, including auditability, monitoring, risk controls, and operational guardrails.
• Partner with engineering, automation, data, and business teams to identify opportunities and deliver AI-driven capabilities.

Required Qualifications

• 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 quickly with minimal onboarding and ramp-up time.
• Experience building and deploying solutions in regulated or highly governed enterprise environments.
• Strong understanding of security controls, compliance requirements, access management, and operational governance.
• Comfort working within structured delivery processes and change-control frameworks.
• Strong communication and stakeholder management skills.
• Capability to translate business challenges into practical AI-enabled solutions.
• Experience collaborating with technical and non-technical audiences.
• 5+ years of experience in software engineering, automation engineering, or a related technical discipline.
• At least 2 years 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 in public cloud environments such as Azure, Google Cloud Platform, Vertex AI, or equivalent technologies.
• Ability to evaluate AI use cases pragmatically, including determining when traditional engineering approaches may be more effective.
• Self-directed ability to independently lead technical initiatives in a fast-moving environment.

Technologies

• Claude, Gemini
• Python
• Azure
• Google Cloud Platform
• Vertex AI
• LLM ecosystems
• Model Context Protocol (MCP)
• RAG architectures
• Vector databases, embeddings
• Semantic search solutions
• RBAC

Preferred Qualifications

• 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.
• Prior experience supporting organizations operating in highly regulated industries such as insurance, financial services, healthcare, or similar sectors.

Location and Compensation

Location: Chicago, IL (onsite)

Compensation: USD 52 - 70 per hour

Minimum Experience: 5 years