Senior AI Engineer, Internal AI Platforms

United States·Los AngelesFull-timesenior

Machine Learning EngineerData

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Overview

Hermeus is a venture-backed defense aviation company reclaiming the lost art of rapid iterative prototyping to build the fastest aircraft in the world today.

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Machine Learning EngineerData

Hermeus is a venture-backed defense aviation company reclaiming the lost art of rapid iterative prototyping to build the fastest aircraft in the world today. By prioritizing relentless hardware iteration, we deliver high-speed systems at the pace of the modern battlefield. We work with the Department of War to provide the high-speed capabilities our nation and its allies need to maintain a durable, asymmetric advantage.

About the Role

~3 min read

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

Aerospace, defense, national security, financial services, healthcare, or other regulated industry experience

Experience with AWS-native AI and infrastructure services including Bedrock, SageMaker, EKS, OpenSearch, or GovCloud

Familiarity with commercial and open-source model providers such as Anthropic Claude, OpenAI, Llama, Mistral, or similar

Experience with AI orchestration and agent frameworks such as LangChain, LlamaIndex, Semantic Kernel, CrewAI, or similar tooling

Experience with vector databases and search technologies such as OpenSearch, Pinecone, Weaviate, pgvector, or FAISS

Experience building AI evaluation pipelines including regression testing, retrieval scoring, and red-team validation

Familiarity with secure software development, DevSecOps, CI/CD, infrastructure as code, and observability tooling

Experience designing systems for CUI, ITAR, export-controlled, or otherwise sensitive data environments

Strong communication skills with the ability to explain AI architecture, risks, and tradeoffs to technical and non-technical stakeholders

U.S. EXPORT CONTROL COMPLIANCE STATUS

The person hired will have access to information and items subject to U.S. export controls, and therefore, must either be a “U.S. person” as defined by 22 C.F.R. § 120.62 or otherwise eligible for deemed export licensing. US persons include U.S. citizens, U.S. nationals, lawful permanent residents (green card holders), and asylees and refugees with such status granted, not pending.

EQUAL OPPORTUNITY

Hermeus is an Equal Opportunity Employer. Employment decisions at Hermeus are based solely on merit, competence, and qualifications, without regard to race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.