AI Engineer at SFE
About the role
Must Have Technical/Functional Skills Strong experience in designing, developing, and deploying Generative AI and Machine Learning solutions on AWS using Bedrock, SageMaker, Python, MLOps, and cloud-native architecture Python, PySpark, SQL Machine Learning, Deep Learning, NLP Generative AI, LLMs, Prompt Engineering Amazon Bedrock, AWS SageMaker RAG (Retrieval Augmented Generation), AI Agents LangChain, LangGraph, LlamaIndex AWS Services: S3, Lambda, IAM, RDS, CloudWatch MLOps, MLflow, CI/CD Pip…
Interview process at SFE
General interview process (this company's specific loop isn't published - reach out if you have insider info).
- Recruiter phone screen - typically 20-40 min
- Technical screen - 1 coding problem or take-home; format varies by company
- Onsite / virtual loop - typically 4-6 rounds over 2-3 weeks; exact split of coding, systems design, and behavioral varies by role and location
Platforms used: unknown — MiPrep tested compatible with major platforms
How to prepare
MiPrep helps you rehearse the specific cadence and question types SFE interviewers score on. Upload your resume and this job description; MiPrep generates a rehearsed answer set in your voice from your own projects.