Lead AWS AI Engineer

Position type: W2 position

Start Date Immediate

Mandatory skills: AWS AI stack, Amazon Transcribe, Amazon Comprehend, Amazon Bedrock

Role Summary

We are seeking an experienced AWS AI Engineer Lead to design, develop, and lead enterprise-scale AI/ML solutions on AWS.

The ideal candidate will have strong expertise in the AWS AI stack, with hands-on experience in Amazon Transcribe, Amazon Comprehend, and Amazon Bedrock, along with a proven ability to architect and deploy intelligent, scalable, and secure cloud-native solutions.

Key Responsibilities

• Lead the design and implementation of AI/ML solutions using AWS services.
• Architect and build intelligent applications leveraging the AWS AI stack.
• Develop and integrate solutions using:Amazon Transcribe for speech-to-text and audio processing use cases
• Amazon Comprehend for natural language processing, sentiment analysis, entity recognition, and text analytics
• Amazon Bedrock for building generative AI applications using foundation models
• Collaborate with business, product, and engineering teams to identify AI-driven opportunities and translate requirements into scalable solutions.
• Design end-to-end data and AI workflows, including ingestion, preprocessing, model integration, and deployment.
• Ensure AI solutions meet security, compliance, performance, and cost-optimization requirements.
• Guide the team on best practices for AWS architecture, MLOps, and AI solution deployment.
• Provide technical leadership, mentoring, and code/design reviews for junior engineers.
• Evaluate emerging AWS AI/ML services and recommend innovative solutions for business needs.

• Strong experience as an AWS AI Engineer / Lead AI Engineer / Solution Architect.
• Deep hands-on expertise in the AWS AI stack, especially:
• Amazon Transcribe
• Amazon Comprehend
• Amazon Bedrock
• Strong understanding of AI/ML solution architecture on AWS.
• Experience building NLP, speech analytics, and generative AI applications.
• Proficiency in Python and working knowledge of APIs, SDKs, and cloud-native integrations.
• Experience with AWS services such as Lambda, S3, API Gateway, Step Functions, IAM, CloudWatch, and SageMaker.
• Knowledge of prompt engineering, foundation models, and LLM-based application development.
• Experience with CI/CD, DevOps, and MLOps practices in cloud environments.
• Strong understanding of security, scalability, and cost optimization in AWS.
• Excellent problem-solving, leadership, and stakeholder management skills.

• AWS certifications such as AWS Certified Machine Learning Specialty or AWS Certified Solutions Architect.
• Experience with enterprise AI transformation programs.
• Familiarity with vector databases, RAG architectures, and conversational AI solutions.
• Experience in deploying production-grade generative AI solutions.