Senior AI Engineer, Internal AI Platforms
Role details
Job location
Tech stack
Job description
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., * 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, Senior AI Engineer IV - $167,450 - $226,550 The salary information provided is a general guideline only. Hermeus takes various factors into account, including, but not limited to, the position's scope and responsibilities, the candidate's professional background, education and training, essential skills, and market and business considerations, when presenting a job offer.
Requirements
Do you have experience in Systems integration?, 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., * 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
Benefits & conditions
$136,000 - $226,550 a year - Full-time, Pulled from the full job description
- Pet insurance
- Paid parental leave
- Parental leave
- 401(k)
- Health insurance
- Paid time off
- Stock options, Compensation is only one part of our total rewards package. Hermeus offers competitive base pay and equity, generous parental leave, potential for year-end bonuses, and more!
- 100% employer-paid health care
- 401k & Retirement Plans
- Weekly Paid Office Lunches
- End of Year Bonuses
- Fully stocked breakrooms
- Stock Options
- Paid Parental Leave
- Unlimited PTO (exempt) and generous accrued PTO (non-exempt), plus 12 federal holidays off
- Pet Insurance