Most boards and executives are currently flying blind when it comes to cyber risk. They are guessing. At Safe, we’ve built an AI\-driven engine that finally gives the C\-Suite a clear, quantified, and real\-time view of their security posture. We don’t just provide data; we provide **certainty**.
We are a **$170M Series C\-funded** category leader. We don’t play in the mid\-market; we operate at the highest levels of global enterprise. Today, we are proud to **serve 10% of the Fortune 500**, protecting global icons such as **Apple, Netflix, AT\&T, Verizon, and Victoria’s Secret**.
As we scale toward our next chapter, we are looking for high\-performers who want to do the best work of their careers at the intersection of AI and Cybersecurity.
### **The Culture Memo: Our Operating System**
Safe is not a typical corporate environment. We are a high\-intensity, mission\-driven team. We value builders who want to define a category and work alongside people who are equally committed to excellence.
- **Extreme Ownership:** We don’t do "not my job." We hire people who see a gap and own the solution from start to finish.
- **The Elite Standard:** We serve the most sophisticated companies on the planet. Our work must be bulletproof. Whether it’s a line of code or a sales deck, we aim for Tier\-1 quality every time.
- **Methodology \& Rigor:** We don’t wing it. From **Force Management** and **MEDDICC** in sales to **data\-driven sprints** in engineering, we rely on proven frameworks to stay disciplined and predictable.
- **Radical Candor:** We move too fast for politics or sugar\-coating. We value direct, honest feedback that helps us find the right answer quickly.
- **The Series C Hustle:** We have the stability of a well\-funded leader but the heart of a startup.
### **The Perks \& Ownership:**
We want our team to feel like owners because they **are** owners. We trust our people to manage their results and their time.
- **Meaningful Equity:** Every "Safestar" is a shareholder. You aren’t just an employee; you are a partner in our success.
- **Unlimited Leaves:** We don’t believe in clock\-watching. We offer **unlimited leave** because we trust you to take the time you need to recharge while staying committed to the mission.
- **Comprehensive Benefits:** We provide top\-tier medical insurance and wellness benefits to ensure you and your family are well cared for.
- **Career Trajectory:** We are growing aggressively. For high\-performers, the path for advancement moves at the speed of your ambition.
As a Principal Engineer \- AI, you will define and lead the technical direction of AI systems that power Safe’s CRQ, CTEM, and TPRM products, including agentic workflows, RAG pipelines, LLM orchestration, and AI\-native developer tooling. You’ll be the hands\-on architect behind Safe’s AI engineering stack, bridging model intelligence with production\-grade infrastructure.
You’ll collaborate with product, data, and platform teams to design scalable, explainable, and enterprise\-ready systems.
This is a high\-impact, technical leadership role that will shape how AI is built, deployed, and governed across Safe.
### **Core Responsibilities:**
- **Architect Safe’s AI Systems:** Design and scale AI\-driven components — LLM orchestration, retrieval\-augmented generation (RAG), vector stores, prompt pipelines, and AI microservices. Drive architecture for AI observability, safety, and evaluation (precision, recall, F1, hallucination detection, cost metrics).
- **Productionize AI Agents:** Build multi\-turn, goal\-oriented agent systems that automate reasoning across TPRM, CTEM, and CRQ domains (e.g., control reviews, issue RCA, automated responses). Ensure reliability, traceability, and deterministic behavior in production.
- **AI Infrastructure \& Platform Ownership:** Partner with Platform \& DevOps teams to operationalize model serving (AWS SageMaker, Bedrock, or self\-hosted Llama), build AI APIs, and manage model lifecycle and versioning. Establish feature stores, embedding management, and in\-memory retrieval layers.
- **Data Pipeline \& Knowledge Graph Integration:** Work with Data Engineering to design pipelines for structured and unstructured data ingestion, semantic indexing, and context retrieval (Snowflake \+ Iceberg \+ LlamaIndex).
- **AI Evaluation, Monitoring \& Governance:** Define internal frameworks for golden dataset validation, LLM evaluation (LangFuse/LangSmith), and safety enforcement policies. Implement human\-in\-the\-loop (HITL) mechanisms and continuous feedback loops.
- **Mentor \& Multiply:** Guide AI and backend engineers on architectural design, experimentation methodologies, and prompt optimization. Collaborate with product leaders to translate abstract AI goals into measurable engineering deliverables.
### **Minimum Qualifications:**
- Experience: 12\+ years total experience in software engineering, including 4\+ years building AI/ML systems or large\-scale data/LLM infrastructure.
- Core Technical Skills:
- Strong programming fundamentals in Python, Go, or TypeScript
- Deep understanding of LLM\-based architectures, prompt engineering, and RAG pipelines
- Hands\-on experience with LangChain, LlamaIndex, or equivalent orchestration frameworks
- Vector databases (FAISS, Pinecone, Weaviate, Redis Vector, or Milvus)
- Cloud model deployment (AWS SageMaker, Bedrock, Vertex AI, or custom inference APIs)
- Data systems: Snowflake, Iceberg, S3, Postgres/MySQL
- MLOps \& Infra: Familiar with model versioning, CI/CD for ML, and performance optimization for real\-time inference.
- Applied AI Focus: Practical understanding of evaluation metrics, hallucination detection, RAG reliability, and enterprise AI safety.
### **Preferred Qualifications:**
- Experience integrating AI into cybersecurity or risk management products
- Familiarity with multi\-agent systems and autonomous workflows (CrewAI, LangGraph, AutoGen)
- Experience building AI evaluation dashboards and AI observability stacks
- Knowledge of knowledge graphs, semantic search, or retrieval pipelines
- Exposure to data governance, compliance, or SOC2/ISO 27001 environments
- Published research, open\-source contributions, or prior leadership of AI teams is a strong plus
If you’re passionate about cyber risk, thrive in a fast\-paced environment, and want to be part of a team that’s redefining security, **we want to hear from you!**