Job Description (JD) – Amazon Bedrock Architect
Job Title - Amazon Bedrock Architect / GenAI Solutions Architect
Location -Remote / Hybrid
Experience
12+ years in IT, with 3+ years in Generative AI, Machine Learning, or AI Platform Architecture
Key Responsibilities
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:
o Amazon Bedrock
o Bedrock Agents
o Bedrock Knowledge Bases
o Bedrock Guardrails
o Amazon OpenSearch
o AWS Lambda
o API Gateway
o Amazon S3
o 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
