Overview
Skills
Job Details
Role :Gen AI expert
Location :Whippany, NJ
requirement.
Job Description:
Core Responsibilities
Design and implement end-to-end GenAI solutions using AWS Bedrock, incorporating foundation models like Claude and Titan, etc.
Develop and optimize prompt engineering strategies for various use cases and business requirements
Experience with RAG (Retrieval-Augmented Generation) implementations
Create and maintain vector search solutions using AWS OpenSearch and other vector databases
Implement and manage knowledge bases using Amazon Kendra for enterprise search solutions
Design and deploy serverless architectures using AWS Lambda and ECS for AI applications
Experience with AI system troubleshooting and debugging
Develop and maintain Infrastructure as Code using CloudFormation
Implement secure and scalable database solutions using RDS PostgreSQL
Build RESTful APIs and microservices for AI application integration
Design and implement NLP pipelines using AWS Comprehend & Guardrails
Develop cost optimization strategies for AI service usage
Lead proof-of-concept development for innovative AI solutions
Implement automated model evaluation frameworks
Required Technical Skills
5+ years of experience in software development with Python
3+ years of hands-on experience with AWS services
Deep expertise in:
o AWS Bedrock and foundation models (Claude, Titan, etc.)
o Vector databases and embedding models
o Amazon Kendra implementation and optimization
o OpenSearch configuration and management
o Serverless architectures (Lambda, ECS)
o RDS PostgreSQL database design and optimization
o AWS Step Functions for AI workflows
o AWS Secrets Manager and Parameter Store
o AWS Comprehend and Guardrails
o Amazon CloudWatch for monitoring AI applications
o Container orchestration with ECS/EKS
o Amazon Athena for data analysis
o AWS Auto Scaling configurations
Essential Knowledge Areas
Advanced understanding of prompt engineering techniques and best practices
Comprehensive knowledge of LLM capabilities, limitations, and optimal use cases
Experience with RAG (Retrieval-Augmented Generation) implementations
Expertise in vector similarity search and semantic search concepts
Strong understanding of AI/ML deployment patterns and architectures
Knowledge of AI security best practices and responsible AI principles
Expertise in AI model evaluation and performance metrics
Understanding of AI model governance and compliance requirements
Knowledge of AI/ML cost optimization techniques
Understanding of AI data privacy and security considerations
Experience with AI model monitoring and debugging
Expertise in model serving architectures
Knowledge of PII detection and redaction
Expertise in implementing AI Guardrails
Knowledge of model performance optimization
Expertise in data preprocessing pipelines
Understanding of model evaluation metrics
Soft skills
Strong problem-solving and analytical abilities
Excellent communication skills for explaining technical concepts to non-technical stakeholders
Ability to lead technical discussions and mentor team members
Strong documentation and technical writing skills
Experience working in Agile environments
Leadership skills for guiding AI initiatives
Ability to influence and drive technical decisions
Strong presentation skills for executive-level communications
Excellent project management capabilities
Capacity to work effectively in cross-functional teams
Ability to mentor and guide junior AI developers
Skills in facilitating technical design sessions
Experience in conducting technical interviews
Conflict resolution abilities
Strategic thinking capabilities
Change management skills
Risk assessment abilities
Decision-making capabilities
Time management skills
Team building abilities