Principal AI Engineer

Roles and Responsibilities

• Define enterprise-wide architecture for GenAI systems, agent frameworks, LLM integration, and multi-agent orchestration
• Establish AI governance standards including security, ethical usage, context management (MCP), agent-to-agent protocols (A2A), and explainability
• Lead evaluation and integration of emerging AI tooling and frameworks, from retrieval infrastructure to observability platforms
• Serve as a cross-functional advisor on LLM implementation across product teams, engineering pods, and data science
• Develop reusable components, SDKs, or templates that standardize GenAI deployment patterns
• Review and challenge architectural proposals from Lead Engineers and ensure alignment with long-term AI strategy
• Build and drive internal capability around GenAI innovation, including mentoring, tech talks, and hackathons
• Support cross-region scalability, data sensitivity considerations, and deployment performance benchmarking
• Stay abreast of industry trends and translate them into actionable design or investment recommendations

Required Skills:

• 8+ years of experience in AI/ML system design, with solid implementation in GenAI, LLMs, or agentic architectures
• Proven experience in architecting production-grade GenAI platforms or frameworks at scale
• Deep proficiency in Python, with mastery over GenAI libraries: OpenAI, transformers, Pydantic, Lang chain, faiss, pinecone, etc.
• Demonstrated experience integrating AI into cloud environments (Azure preferred: Databricks, Azure Foundry)
• Strong knowledge of AI security, privacy frameworks, hallucination mitigation, and governance