What are the responsibilities and job description for the Sr Artificial Intelligence / AI Developer -CTH - F2F Interview position at Keylent?
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