What are the responsibilities and job description for the GenAI Architect position at Siri InfoSolutions Inc ?
Job title : GenAI Architect
Location : Whippany NJ (onsite)
Duration : Long term
Must skills :
8 years of experience in software development with Python 5 years of handson experience with AWS services Deep expertise in : AWS Bedrock and foundation models (Claude Titan etc.)
Vector databases and embedding models Amazon Kendra implementation and optimization OpenSearch configuration and management AWS CloudFormation and Infrastructure as Code Serverless architectures (Lambda ECS) IAM security and best practices RDS PostgreSQL database design and optimization AWS Step Functions for AI workflows AWS API Gateway configuration AWS Secrets Manager and Parameter Store AWS Comprehend and Guardrails Amazon CloudWatch for monitoring AI applications Container orchestration with ECS / EKS AWS Glue for ETL processes Amazon Athena for data analysis AWS Auto Scaling configurations Amazon ECR for container registry Experience with enterprisescale AI implementations Job Description :
Core Responsibilities
Design and implement endtoend 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 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 Develop and maintain Infrastructure as Code using CloudFormation Implement secure and scalable database solutions using RDS PostgreSQL Configure and manage IAM roles and permissions for secure AI service access Build RESTful APIs and microservices for AI application integration Design and implement NLP pipelines using AWS Comprehend & Guardrails Create automated testing frameworks for AI applications Develop cost optimization strategies for AI service usage Lead proofofconcept development for innovative AI solutions Implement automated model evaluation frameworks Design and maintain model serving architectures Create model monitoring and alerting systems Develop custom metrics for AI system performance Implement model governance frameworks 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 (RetrievalAugmented 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 Understanding of model governance frameworks Required Experience
Proven track record of successfully delivered GenAI projects Experience with enterprisescale AI implementations Background in creating productionready AI solutions History of optimizing AI model performance and cost Experience with realtime AI inference systems Track record of successful AI system architecture design Experience with AI system performance tuning Background in AI project estimation and planning History of successful stakeholder management in AI projects Experience with AI system troubleshooting and debugging Track record of successful model deployments Experience with model monitoring systems Background in model governance implementation History of successful model optimization Track record of successful data pipeline design Background in model experiment design Background in model performance optimization Background in model governance frameworks Soft Skills
Strong problemsolving and analytical abilities Excellent communication skills for explaining technical concepts to nontechnical 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 executivelevel communications Excellent project management capabilities Capacity to work effectively in crossfunctional 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 Decisionmaking capabilities Time management skills Team building abilities Additional Requirements
Bachelors or Masters degree in Computer Science Software Engineering or related field Ability to work in a fastpaced environment with rapidly evolving technologies Willingness to stay current with AWS AI service updates and new features Availability for occasional offhours support during critical deployments Ability to work across different time zones if necessary Commitment to continuous learning and professional development Willingness to contribute to technical blogs and knowledge sharing Key Skills
APIs,Pegasystems,Spring,SOAP,.NET,Hybris,Solution Architecture,Service-Oriented Architecture,Adobe Experience Manager,J2EE,Java,Oracle
Employment Type : Full Time
Vacancy : 1
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