Overview
Skills
Job Details
GenAI Expert
Location: Whippany, NJ (Hybrid)
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