Senior AI Engineer, Internal AI Platforms in Los Angeles, California at Hermeus

We are seeking a Senior AI Engineer, Internal AI Platforms to help design, build, and scale Cortex, our internal AI platform. Cortex is intended to become the centralized AI platform across the company - enabling employees to securely interact with internal knowledge, business systems, workflows, and future agentic capabilities within a highly governed environment.

This is a hands-on engineering role focused on building secure, scalable, production-grade AI systems for enterprise use. The ideal candidate has experience developing LLM-enabled applications, retrieval systems, and agentic workflows within regulated or security-conscious environments, and is comfortable operating across architecture, infrastructure, integrations, observability, and user experience.

• Design, build, and improve Cortex, including retrieval systems, document analysis, workflow automation, and internal AI capabilities
• Develop integrations with enterprise platforms such as Jira, Confluence, Microsoft 365, Slack/GovSlack, and internal business systems
• Build and optimize RAG pipelines including ingestion, chunking, embeddings, vector search, permissions enforcement, and response evaluation
• Develop agentic workflows that safely perform actions such as summarization, ticket updates, governed data access, and business process automation
• Define architecture for secure self-hosted, private, or cloud-isolated AI systems within regulated environments
• Partner with Security, IT, and Compliance teams to implement governance controls, auditability, permissions, and secure API access
• Evaluate and integrate commercial, open-source, and cloud-native LLM providers and orchestration frameworks
• Build observability into AI systems including monitoring, evaluation metrics, latency tracking, error handling, and workflow reliability
• Contribute reusable AI engineering standards, patterns, and platform capabilities to support long-term internal AI adoption

• 5+ years of professional software engineering experience
• 2+ years building AI, ML, automation, or LLM-enabled applications in production environments
• Strong programming experience in Python, TypeScript, or both
• Hands-on experience building production AI systems using LLMs, RAG pipelines, vector databases, embeddings, and orchestration frameworks
• Experience deploying scalable services in cloud or private infrastructure environments, preferably AWS
• Experience building AI systems that integrate with enterprise platforms, APIs, and governed data sources
• Strong understanding of security, permissions models, identity management, and enterprise data governance
• Practical understanding of LLM limitations including hallucinations, prompt injection, data leakage, and evaluation challenges
• Ability to operate in ambiguity, rapidly prototype solutions, and harden successful systems into production-ready platforms