Principal AI Engineer

Key Responsibilities & Skills

• AI-driven SDLC
• AI Platform Architecture Design
• Engineering Quality & Observability
• Production AI System Development
• Retrieval-Augmented Generation (RAG) Pipelines
• LLM Evaluation Frameworks
• Guardrails & AI Safety Standards
• Agentic System Development
• Generative AI Product Design
• Technical Standards Enforcement
• MLops
• Modern Life Cycle Management
• Guardrails
• AI safety standards
• Engineering Quality
• Observability
• Vector Search
• Embedded Infrastructure
• AI Safety Standards

Technical Skills

• Python
• Vector Search Engines
• MLOps Platforms
• CI/CD (GitHub Actions)
• APIs / REST / gRPC
• Event-Driven Architecture (Kafka / PubSub)
• Observability Tools (Prometheus / Grafana)
• Microsoft Office Suite / Google Workspace
• Claude Code
• GitHub Copilot
• Cursor
• LangChain
• LlamaIndex
• AWS
• Google Cloud Platform
• Azure
• TensorFlow
• PyTorch
• APIs
• REST
• gRPC
• Kafka
• PubSub
• Promethrus
• Grafana

Education

Bachelor's Degree in Computer Science, Software Engineering, Electrical Engineering, Artificial Intelligence, Machine Learning. Preferred: Master's in Computer Science, Master's in Artificial Intelligence, PhD in Computer Science, PhD in Machine Learning, PhD in AI.

Industry Experience

• E-commerce
• AI / GenAI Platforms
• Large-Scale Distributed Systems
• Cloud Services
• SaaS
• Enterprise Software