What are the responsibilities and job description for the Python + GenAI AWS Engineer (Lead Data Engineer + Data Science) position at Clairvoyant AI, Inc.?
Job Details
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Job Title: Python GenAI AWS Engineer (Lead Data Engineer Data Science)
Experience Level: 10 years
Location: Jersey City, NJ
Duration : 6 Months Contract
Job Overview:
We are looking for a highly skilled Python GenAI AWS Engineer to join our dynamic team. The ideal candidate will have a strong background in Python, Generative AI models, and cloud infrastructure (AWS). This individual will contribute to developing, deploying, and optimizing DE solutions in the cloud, leveraging cutting-edge AI technologies and scalable cloud resources.
Key Responsibilities:
Develop and implement AI/ML solutions using Python and Generative AI technologies (e.g., GPT, LLMs, BERT).
Design, deploy, and manage scalable solutions on AWS (Lambda, S3, EC2, RDS, SageMaker, etc.).
Optimize and monitor AI models in production, ensuring they meet performance, cost, and accuracy targets.
Develop API integrations for AIpowered applications, leveraging cloudnative tools and serverless architecture.
Ensure security and compliance in AI/ML workloads following best practices for data governance and cloud security.
Work closely with DevOps and MLOps teams to ensure efficient CI/CD pipelines for model deployment and continuous improvement.
Document technical solutions and provide support and mentorship to junior team members.
Key Requirements:
8 years of hands on experience in Python development, with a focus on GenAI applications.
Proven expertise in Generative AI models (e.g., GPT, Transformer models, GANs, or similar) and familiarity with finetuning and model optimization techniques.
Strong experience with AWS services like Lambda, Sage Maker, EC2, S3, RDS, API Gateway, and IAM.
Experience with API development and serverless architecture on AWS.
Knowledge of cloud infrastructure best practices, including cost optimization, monitoring, and scaling.
Strong understanding of MLOps/DevOps pipelines in cloud environments, including Docker, Kubernetes, and CI/CD practices.
Excellent problem solving and communication skills, with the ability to work in a collaborative environment.
Nice to Have:
Certifications in AWS (AWS Certified Solutions Architect/Developer).
Experience in Natural Language Processing (NLP) and Conversational AI applications.
Familiarity with data engineering tools such as Airflow, Spark, PySpark, or similar.
Experience with AI model explainability and ethical AI considerations.
Education:
Bachelor s or Master s degree in Computer Science, Data Science, AI, or a related field.
