AWS Bedrock

Job Description

JD is below:

Design, develop, and deploy generative AI based applications using AWS Bedrock.
Proficiency in prompt engineering and RAG pipeline
Experience in building Agentic Generative AI applications
Fine-tune and optimize foundation models from AWS Bedrock for various use cases.
Integrate generative AI capabilities into enterprise applications and workflows.
Collaborate with cross-functional teams, including data scientists, ML engineers, and software developers, to implement AI-powered solutions.
Utilize AWS services (S3, Lambda, SageMaker, etc.) to build scalable AI solutions.
Develop APIs and interfaces to enable seamless interaction with AI models.
Monitor model performance, conduct A/B testing, and enhance AI-driven products.
Ensure compliance with AI ethics, governance, and security best practices.
Stay up-to-date with advancements in generative AI and AWS cloud technologies.

Required Skills & Qualifications:

Bachelor’s or Masters degree in Computer Science, AI, Machine Learning, or a related field.
3+ years of experience in AI/ML development, with a focus on generative AI.
Hands-on experience with AWS Bedrock and foundation models.
Proficiency in Python and ML frameworks.
Experience with AWS services such as SageMaker, Lambda, API Gateway, DynamoDB, and S3.
Experience with prompt engineering, model fine-tuning, and inference optimization.
Familiarity with MLOps practices and CI/CD pipelines for AI deployment.
Ability to work with large-scale datasets and optimize AI models for performance.
Excellent problem-solving skills and ability to work in an agile environment.

Preferred Qualifications:

AWS Certified Machine Learning – Specialty or equivalent certification.
Experience in LLMOps and model lifecycle management.
Knowledge of multi-modal AI models (text, image, video generation).
Hands-on experience with other cloud AI platforms (Google Vertex AI, Azure OpenAI).
Strong understanding of ethical AI principles and bias mitigation techniques.