Amazon Bedrock Architect

Key Responsibilities

• Solution Architecture & Design
• Generative AI Engineering
• Security, Governance & Compliance
• Integration & Automation
• AI Operations & Optimization
• Leadership & Consulting

Solution Architecture & Design

• Design and implement enterprise Generative AI platforms using Amazon Bedrock.
• Architect scalable, secure, and highly available AI solutions aligned with AWS Well-Architected principles.
• Define reference architectures for Agentic AI, RAG, AI Assistants, Intelligent Search, and Enterprise Knowledge Platforms.
• Evaluate and recommend appropriate Foundation Models based on use case, cost, latency, and performance requirements.

Generative AI Engineering

• Design and deploy solutions using:
• Amazon Bedrock
• Bedrock Agents
• Bedrock Knowledge Bases
• Bedrock Guardrails
• Amazon OpenSearch
• AWS Lambda
• API Gateway
• Amazon S3
• Step Functions
• Implement advanced prompting strategies, AI orchestration, and multi-agent workflows.
• Build Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge repositories.

Security, Governance & Compliance

• Establish AI governance frameworks, security controls, and Responsible AI practices.
• Implement Bedrock Guardrails to protect against prompt injection, harmful content, and sensitive data exposure.
• Design AI solutions compliant with enterprise security standards, regulatory requirements, and data privacy controls.

Integration & Automation

• Integrate AI solutions with enterprise applications, APIs, ServiceNow, Jira, ITSM platforms, and business workflows.
• Design automated decision-making and action-execution frameworks using Bedrock Agents and AWS services.
• Enable conversational AI capabilities across operations, support, and business functions.

AI Operations & Optimization

• Define AI observability and monitoring frameworks.
• Track model performance, latency, token utilization, hallucination rates, and operational metrics.
• Optimize AI workloads for cost, scalability, and reliability.
• Collaborate with FinOps teams to manage AI consumption and governance.

Leadership & Consulting

• Partner with business stakeholders to identify high-value AI use cases.
• Lead architecture reviews, technical workshops, and AI strategy sessions.
• Mentor architects, engineers, and data scientists on AWS Generative AI best practices.
• Provide executive-level recommendations on AI adoption and roadmap planning.

Experience

• 12+ years of experience in Cloud Architecture, Solution Architecture, or Enterprise Architecture.
• Hands-on experience delivering enterprise AWS cloud solutions.
• Proven experience designing Generative AI applications in production environments.
• Experience with AI/ML, NLP, and Large Language Models (LLMs).

Technical Skills

• Amazon Bedrock
• Bedrock Agents
• Bedrock Knowledge Bases
• Bedrock Guardrails
• AWS Lambda
• API Gateway
• Step Functions
• Amazon OpenSearch
• Amazon S3
• Amazon EKS / ECS
• Python
• LangChain / LangGraph
• Vector Databases
• RAG Architecture
• Prompt Engineering
• Foundation Models (Claude, Titan, Nova, Llama, Mistral)
• CI/CD and Infrastructure as Code (Terraform, CloudFormation)

Preferred Qualifications

• AWS Certified Solutions Architect – Professional
• AWS Certified Machine Learning Engineer or Specialty
• TOGAF Certification
• Experience with MLOps / LLMOps platforms
• Experience implementing Agentic AI architectures
• Knowledge of FinOps and AI cost optimization
• Public sector, healthcare, financial services, or regulated industry experience