AI Engineer

Top 5 Skills

• Production Experience with atleast 2 Agentic deployments
• Deep understanding of harness engineering, grounding and evaluation
• Strong python programming and pydyantic/ Langraph framework
• LLM Ops, pipelines
• Clear and strong verbal communication
  

Required Qualifications

• Experience: 8+ years of progressive experience in Data Science, Machine Learning, or Applied AI research, with a minimum of 3 years in a leadership or principal role.
• Technical Depth: Expert proficiency in Python and ML frameworks (PyTorch, TensorFlow). Deep knowledge of statistical modeling, machine learning fundamentals, and distributed computing.
• Ownership Track Record: Demonstrated history of successfully taking ownership of complex, ambiguous AI projects and driving them from initial concept/POC to stable production release.
• Architecture: Strong understanding of Microservices architecture and experience designing cloud-native ML solutions (AWS, GCP, or Azure).
• Communication: Exceptional ability to distill complex technical and mathematical concepts into clear business implications for executive leadership.
• Education: Master’s or Ph.D. in Computer Science, Applied Mathematics, Engineering, or a related quantitative field.