AWS Bedrock

Tekskills Inc.; Kolkata District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Tekskills Inc. in Kolkata invites a talented AI/ML engineer to design, develop, and deploy generative AI solutions using AWS Bedrock. You will craft prompts, optimize models, and build scalable AI-enabled workflows for enterprise environments.

The ideal candidate has 3+ years in AI/ML, strong Python skills, and hands-on experience with AWS Bedrock, SageMaker, Lambda, and API Gateway. Collaboration with data scientists, ML engineers, and software developers is essential.

Qualifications

• Bachelor's or Master's 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.

Responsibilities

• Design, develop, and deploy generative AI 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.

Skills

Python

AWS Bedrock

Prompt engineering

RAG pipelines

Foundation models

API development

ML frameworks

MLOps

Education

Bachelor's or Master's in CS/AI

Tools

AWS SageMaker

AWS Lambda

API Gateway

DynamoDB

S3

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.