What are the responsibilities and job description for the AI Solutions Architect ? Agentic Optimization & Explainable AI (AWS) position at Jobs via Dice?
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Role Overview:
Design and architect an AI-enabled optimization solution that integrates with third-party engines to automate back-office processes, ensuring a scalable, secure, regulatory compliance and explainable AI foundation.
Key Responsibilities:
Design the overall architecture for the agentic AI platform leveraging company AI assets and solution accelerators
Define integration patterns between LLMs, specialized models, and external engines
Establish AI governance frameworks and responsible AI controls
Create technical specifications for agent orchestration and workflows
Ensure solution meets security, PII, scalability, and performance requirements
Guide the development team on AI implementation best practices
Design explainability components for AI-driven decisions
Required Skills:
8 years of experience in software architecture with 3 years in AI/ML systems
Deep expertise in LLM integration, prompt engineering, and agent-based architectures
Experience With Financial Services Applications And Regulatory Requirements
Knowledge of AWS cloud architecture and AI/ML services
Understanding of optimization algorithms and financial modeling
Strong technical leadership and communication skills
Technologies:
AWS services: Lambda, ECS, API Gateway, S3, DynamoDB, SageMaker
LLM platforms: OpenAI GPT models, AWS Bedrock, or approved LLM platforms
Agent orchestration frameworks: LangChain, AutoGen, or similar
Infrastructure as Code: Terraform, CloudFormation
API development: REST, GraphQL
Security frameworks: AWS IAM, KMS, Secret Manager
Monitoring tools: CloudWatch, Prometheus, Grafana
Version control: GitHub Enterprise, TeamCity
Role Overview:
Design and architect an AI-enabled optimization solution that integrates with third-party engines to automate back-office processes, ensuring a scalable, secure, regulatory compliance and explainable AI foundation.
Key Responsibilities:
Design the overall architecture for the agentic AI platform leveraging company AI assets and solution accelerators
Define integration patterns between LLMs, specialized models, and external engines
Establish AI governance frameworks and responsible AI controls
Create technical specifications for agent orchestration and workflows
Ensure solution meets security, PII, scalability, and performance requirements
Guide the development team on AI implementation best practices
Design explainability components for AI-driven decisions
Required Skills:
8 years of experience in software architecture with 3 years in AI/ML systems
Deep expertise in LLM integration, prompt engineering, and agent-based architectures
Experience With Financial Services Applications And Regulatory Requirements
Knowledge of AWS cloud architecture and AI/ML services
Understanding of optimization algorithms and financial modeling
Strong technical leadership and communication skills
Technologies:
AWS services: Lambda, ECS, API Gateway, S3, DynamoDB, SageMaker
LLM platforms: OpenAI GPT models, AWS Bedrock, or approved LLM platforms
Agent orchestration frameworks: LangChain, AutoGen, or similar
Infrastructure as Code: Terraform, CloudFormation
API development: REST, GraphQL
Security frameworks: AWS IAM, KMS, Secret Manager
Monitoring tools: CloudWatch, Prometheus, Grafana
Version control: GitHub Enterprise, TeamCity