AI Principal Software Engineer (Remote)

Inspira Financial Trust, LLC; Oak Brook (IL); A distancia; USD 180.000 - 240.000; Jornada completa

Descripción de la vacante

Inspira Financial Trust, LLC is seeking an AI CoE Principal Software Engineer to own the enterprise AI engineering foundation, including semantic routing, model hosting, and AI operations. This senior IC will shape architecture, standards, and a multi-year capability roadmap from discovery through production scale.

You will design, build, and operate the shared AI platform, partner with AI-Ops, and deliver production AI services for documentation, claims adjudication, and regulatory monitoring

Responsabilidades

• Architect, build, and operate the shared enterprise AI platform, including core semantic data, model, harness, and hosting capability used across developer and in-product personalization use cases.
• Design and maintain intelligent request routing using semantic analysis and deterministic logic to direct requests to the best-fit LLM, internal tool, or agentic pool, using cost, latency, and privacy as routing criteria.
• Partner with AI-Ops to enable metric-based reporting, quality, performance, and drift monitoring across live systems, build model evaluation harnesses, and establish governance guardrails for safe AI use at scale.
• Design and implement secure, compliant AI integration patterns appropriate for a regulated financial services environment.
• Build and scale agentic pipelines and multi-agent orchestration across the software development lifecycle, from pilot through measured engineering capacity across product teams.
• Deliver production AI services supporting document intelligence and claims adjudication, conversational and voice self-service, call intelligence, fraud and anomaly detection, and regulatory monitoring.
• Develop reusable reference architectures and standard patterns so other engineering teams and embedded consultants can build AI solutions without rebuilding the foundation.
• Evaluate unit economics for AI workloads, including cost per transaction, token and inference spend, latency budgets, and build-versus-buy and self-host-versus-vendor decisions.
• Identify and prototype emerging AI capabilities relevant to the business and technology roadmap, including fast, focused feasibility spikes with clear recommendations.
• Lead hands-on training sessions and pair directly with engineering teams on new development methods and prototype or pattern adoption.
• Monitor the AI landscape and translate findings into roadmap recommendations on what to pilot, what to watch, and what to decline.
• Set technical direction and standards for embedded AI consultants and the coaching network to scale AI delivery capacity beyond the CoE.
• Mentor senior and lead engineers across business units, review AI designs, and serve as the escalation point for complex agentic and integration issues.
• Partner with security, risk, compliance, and data governance teams to support safe and compliant AI delivery.
• Perform other duties as assigned.

Descripción del empleo

Position Summary

The AI CoE Principal Software Engineer will report to the Sr. Director, AI Center of Excellence, in the Technology Department . This role is the most senior individual contributor on the team and the technical owner of the enterprise AI engineering foundation, including the semantic router, model and harness hosting, the enterprise AI gateway, and the AI operations layer used across the business. The role is responsible for setting AI engineering architecture and standards and then building them, carrying a multi-year capability roadmap from discovery through prototype, validation, and production scale. Primary duties include designing and building the shared AI platform and semantic routing layer; product inference and personali zation, partnering with AI-Ops on monitoring, evaluation, and governance guardrails; building secure, compliant AI integration patterns for a regulated financial services and health and benefits environment s ; leading agentic pipeline and multi-agent orchestration work; delivering production AI services for CoE -enabled business functions; developing reusable reference architectures for other engineering teams; managing AI unit economics; prototyping emerging AI capabilities; mentoring senior and lead engineers; and partnering with security, risk, compliance, and data governance. This role does not have direct reports.

Duties & Responsibilities

• Architect, build, and operate the shared enterprise AI platform, including core semantic data, model, harness, and hosting capability used across developer and in-product personalization use cases.
• Design and maintain intelligent request routing using semantic analysis and deterministic logic to direct requests to the best-fit LLM, internal tool, or agentic pool, using cost, latency, and privacy as routing criteria.
• Partner with AI-Ops to enable metric-based reporting, quality, performance, and drift monitoring across live systems, build model evaluation harnesses, and establish governance guardrails for safe AI use at scale.
• Design and implement secure, compliant AI integration patterns appropriate for a regulated financial services environment.
• Build and scale agentic pipelines and multi-agent orchestration across the software development lifecycle, from pilot through measured engineering capacity across product teams.
• Deliver production AI services supporting document intelligence and claims adjudication, conversational and voice self-service, call intelligence, fraud and anomaly detection, and regulatory monitoring.
• Develop reusable reference architectures and standard patterns so other engineering teams and embedded consultants can build AI solutions without rebuilding the foundation.
• Evaluate unit economics for AI workloads, including cost per transaction, token and inference spend, latency budgets, and build-versus-buy and self-host-versus-vendor decisions.
• Identify and prototype emerging AI capabilities relevant to the business and technology roadmap, including fast, focused feasibility spikes with clear recommendations.
• Lead hands-on training sessions and pair directly with engineering teams on new development methods and prototype or pattern adoption.
• Monitor the AI landscape and translate findings into roadmap recommendations on what to pilot, what to watch, and what to decline.
• Set technical direction and standards for embedded AI consultants and the coaching network to scale AI delivery capacity beyond the CoE .
• Mentor senior and lead engineers across business units, review AI designs, and serve as the escalation point for complex agentic and integration issues.
• Partner with security, risk, compliance, and data governance teams to support safe and compliant AI delivery.
• Perform other duties as assigned.