Principal AI Engineer

Responsibilities:

• Design and implement scalable agentic solutions for diverse use cases
• Leverage a broad stack of Open Source AI technologies to build and maintain a centralized AI platform with unified APIs for cross-functional team access and build various types of agents
• Work with Product Engineers to integrate AI agents into customer-facing applications and internal tools
• Lead technical discussions, mentor junior engineers, and help set the technical vision for the AI platform roadmap.
• Ensure compliance with security, privacy, and regulatory requirements across the software development lifecycle.
• Optimize performance of AI-powered workloads across compute and storage layers using cloud-native and open-source solutions.
• Conduct performance analysis and capacity planning to ensure platform scalability

Relevant experience and educational requirements:

• Bachelors or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of software engineering experience, including 2+ years working on AI/ML platforms or infrastructure.
• Experience in building large-scale distributed systems and microservices.
• Strong programming skills in Python.
• Hands-on experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
• Experience with containerization and orchestration (e.g., Docker, Kubernetes).
• Understanding of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks
• Cloud platform experience (AWS, GCP, or Azure).