Bachelor’sor master’s degree in computer science, Engineering, or a related field.
- Proven experience indesigning and implementing LLM harness engineering patterns and orchestrationtechniques. Experience with AWS and Azure is preferred.
- Strong programming skills in languages such as Python and/or Java.
- Experience with Azure services, including Azure WebApp services, Azure AIServices, Azure Functions, AWS-ECS/EKS, Aws Agentcore and AWS DyanamoDB.
- Familiarity with OpenAI technologies, such as GPT-3/4 and reinforcementlearning frameworks.
- Experience with Large Language model integration with APIs, building AI agentsand working with multi-modal models.
- Proficiency in data preprocessing, feature engineering, and model evaluationtechniques.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to work independently and as part of a team in a fast-pacedenvironment.
PreferredQualifications:
- Experience with AWS services, such as Amazon SageMaker, AWS Lambda, and AWSAI/ML services.
- Knowledge of Google Cloud services, including Google Cloud AI Platform, GoogleCloud Functions, and Google Cloud AutoML.
- Experience with cloud-based deployment and scaling of GenAI applications onAzure, AWS, and Google Cloud.
- Knowledge of containerization technologies such as Docker and Kubernetes.
- Familiarity with DevOps practices and tools for CI/CD pipelines.
- Contributionsto open-source GenAI or cloud service integration projects.
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