Principal Engineer AI

Job Requirements

• 12+ years total experience in software engineering, including 4+ years building AI/ML systems or large-scale data/LLM infrastructure.
• 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 optimisation 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.

Safe Security, a cybersecurity firm incubated at IIT Bombay and backed by John Chambers (Chairman Emeritus, Cisco), provides cyber risk assessment services and platforms globally. Based in Bangalore, India, Safe Security serves Fortune 500 companies and governments. Founded by Saket Modi, Vidit Baxi, and Rahul Tyagi, the company leverages cutting-edge technology to address critical cybersecurity needs.