AI Engineer

Education • Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field
• Strong academic foundation in statistics, probability, and machine learning
Core Experience • 5–8 years of professional experience in Data Science, Machine Learning, or Applied AI
• Hands-on experience building, training, and deploying ML models in production environments
• Strong understanding of data preprocessing, feature engineering, and model evaluation
• Experience working on end-to-end ML workflows under guidance of senior/principal team members
• Ability to translate business and product requirements into data-driven solutions
Machine Learning & MLOps • Practical experience using Amazon SageMaker for:
• Model training and tuning
• Model deployment and inference
• Experience with common ML algorithms using scikit-learn, TensorFlow, or PyTorch
• Familiarity with MLOps concepts such as:  
• Model versioning
• Experiment tracking
• Basic monitoring and retraining workflows
• Working knowledge of Docker and exposure to Kubernetes-based deployments
• Experience collaborating with ML engineers to operationalize models
Generative AI & LLMs • Hands-on experience developing LLM-powered applications using Amazon Bedrock or similar platforms
• Experience building or contributing to Retrieval-Augmented Generation (RAG) pipelines, including:
• Document ingestion and chunking
• Embedding generation
• Similarity search using vector databases
• Practical knowledge of prompt engineering, prompt tuning, and output evaluation
• Understanding of common LLM failure modes such as hallucinations and grounding issues
• Ability to evaluate LLM responses for accuracy, relevance, and safety
Agentic AI (Growing Expertise) • Exposure to Agentic AI concepts and frameworks such as AgentCore
• Experience implementing:  
• Simple Autonomous agents or workflows
• Multi-step reasoning with predefined tools
• Familiarity with tool-calling, agent orchestration, and workflow automation
• Understanding the importance of:  
• Guardrails
• Human-in-the-loop mechanisms
• Logging and observability for agent behavior
Cloud Platform: • Working knowledge of key AWS services, including:
• S3, Lambda, Redshift, IAM
Professional & Collaboration Skills • Strong Python programming skills and experience working with APIs
• Ability to work effectively in cross-functional teams (product, engineering, analytics)
• Willingness to learn quickly in a fast-evolving AI landscape
• Comfortable taking technical guidance and implementing feedback
• Clear communication of findings, limitations, and model behavior to non-technical stakeholders
Nice to Have • Initial exposure to AI governance, compliance, or ethical AI practices
• Experience with monitoring LLM outputs and basic evaluation frameworks
• Certifications in AWS, Machine Learning, or Data Science
• Prior experience in enterprise or cloud-native environments

Experience: 6
Posted: 2026-05-05T12:44:25.897Z