Lead AWS AI Engineer
Location: Piscataway, NJ
Experience level: min 10+ years
Position type: W2 position
Start Date Immediate
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.
Required Skills
- 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.
Preferred Qualifications
- 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.