Principal Engineer, Agentic AI

Design and deliver scalable, secure, production-grade AI/ML architectures and Generative AI applications involving LLMs, RAG pipelines, and agentic orchestration frameworks.

Lead technical strategy, set engineering standards for AI platforms, and guide multiple teams in building reusable GenAI components and workflows.

Translate complex business requirements into durable technical architectures; influence senior stakeholders and unblock engineering challenges across frontend, backend, and AI infrastructure layers.

11+ years total experience in software engineering with strong expertise in Python.

Proven experience architecting and delivering production-grade Generative AI applications at scale with deep knowledge of LLM integration patterns and agentic frameworks (LangGraph, CrewAI, AutoGen).

Hands-on experience with MLOps tools and practices (e.g., MLflow, Vertex AI, Kubeflow), cloud platforms especially GCP and/or Databricks.

Bachelor’s or Master’s degree in Computer Science, IT, or related field.

Experienced in designing end-to-end AI/ML systems combining backend, frontend, and AI infrastructure with a strong system design background.

Capable of defining and driving technical strategy influencing multiple teams with leadership in scalable GenAI platformisation and AI workflow orchestration.

Knowledgeable about enterprise AI security, privacy, compliance, and governance ensuring enterprise readiness in AI deployments.