Sr Artificial Intelligence / AI Developer -CTH - F2F Interview

AI Role
Required Qualifications

Education

· Bachelor’s degree in Computer Science, Data Science, Engineering, Information Technology, or related field.

· Master's degree preferred.

Technical Skills

· Strong hands-on experience developing production-grade applications using Python 3.11+.

· Experience designing and implementing agentic AI systems and intelligent automation workflows.

· Hands-on experience with Amazon SageMaker for machine learning model development, training, deployment, and monitoring.

· Proficiency in Dataiku for data preparation, analytics, and machine learning workflows.

· Strong understanding of:

o Machine Learning algorithms

o Model evaluation techniques

o Feature engineering

o MLOps practices

o Model lifecycle management

· Experience working with AWS Bedrock AgentCore, including Agent Runtime, Memory, Identity, and Tool Gateway capabilities.

· Knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based architectures.

· Experience with multi-agent orchestration frameworks such as:

o LangGraph

o CrewAI

o AutoGen

o Equivalent agent orchestration platforms

· Strong understanding of Model Context Protocol (MCP) and agent tool integration patterns.

· Experience integrating enterprise APIs, databases, and third-party services into AI workflows.

· Familiarity with AWS cloud architecture, serverless services, and scalable application design.

Certifications

Candidates possessing any of the below certifications is a plus:

· AWS Certified Solutions Architect – Associate

· AWS Certified Developer – Associate

· AWS Certified AI Practitioner

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ML Role

Required Qualifications

Education

· Bachelor’s degree in Computer Science, Data Science, Engineering, Information Technology, or related field.

· Master's degree preferred.

Technical Skills

· Strong hands-on experience developing production-grade applications using Python 3.11+.

· Experience designing and implementing agentic AI systems and intelligent automation workflows.

· Hands-on experience with Amazon SageMaker for machine learning model development, training, deployment, and monitoring.

· Proficiency in Dataiku for data preparation, analytics, and machine learning workflows.

· Strong understanding of:

o Machine Learning algorithms

o Model evaluation techniques

o Feature engineering

o MLOps practices

o Model lifecycle management

· Experience working with AWS Bedrock AgentCore, including Agent Runtime, Memory, Identity, and Tool Gateway capabilities.

· Knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based architectures.

· Experience with multi-agent orchestration frameworks such as:

o LangGraph

o CrewAI

o AutoGen

o Equivalent agent orchestration platforms

· Strong understanding of Model Context Protocol (MCP) and agent tool integration patterns.

· Experience integrating enterprise APIs, databases, and third-party services into AI workflows.

· Familiarity with AWS cloud architecture, serverless services, and scalable application design.

Certifications

Candidates possessing any of the below certifications is a plus:

· AWS Certified Solutions Architect – Associate

· AWS Certified Developer – Associate

· AWS Certified AI Practitioner