AI Solutions Architect

Job Summary

Impiricus is moving fast. Our business units (StratOps, Commercial Ops, etc.) are rapidly prototyping highly impactful internal AI tools using the latest vibe coding and agentic engineering techniques. We are hiring an Internal AI Solutions Architect to be the bridge between these grassroots innovations and enterprise-grade stability. Reporting to both the central AI hub team as well as the business unit you support, you will act as a Forward Deployed Engineer (FDE). You will not build foundational models; you will help our commercial team leverage AI to redesign workflows and generate revenue, while supporting business-built prototypes and 'graduating' them into secure, scalable, and maintainable internal products.

Responsibilities

• Prototype Incubation & Auditing: Evaluate 'vibe-coded' AI tools and automations built by non-technical business units (StratOps, Commercial Ops, etc.) to help boost their commercial ROI, security posture, and architectural viability.
• Production Refactoring (The Paved Road): Take ownership of high-value internal prototypes (e.g., AI SDRs, RFP generators) and refactor them into secure, scalable, and enterprise-grade applications.
• LLM Orchestration & Integration: Build and maintain secure integrations between foundational models (via APIs) and Impiricus's internal systems, specifically our Enterprise Data Lake and CRM (Salesforce).
• Full-Lifecycle Maintenance: Act as the technical owner for all 'graduated' internal AI applications, ensuring high uptime, managing prompt drift, and updating API connections as internal schemas change.
• Cross-Functional Product Management: Act as your own PM. Interview business stakeholders to map complex operational bottlenecks, ruthlessly define scope, and manage stakeholder expectations regarding what should be an AI experience versus a standard SQL dashboard.
• Governance Enforcement: Apply Enterprise Data & Analytics standards to all internal tooling, ensuring zero data leakage, strict access controls, and mitigation of hallucination risks in operational outputs.

Requirements

• Applied Engineering Experience: 2+ years of professional experience in software engineering, data engineering, or technical architecture, with a clear track record of building and deploying functional applications.
• AI/LLM Proficiency: Demonstrable, hands-on experience building with LLM orchestration frameworks (e.g., LangChain, LlamaIndex) and managing context windows, pr