Senior AI Solutions Architect - AWS GenAI & Agentic AI

Sr Architect

Area(s) of responsibility

Key Responsibilities

GenAI & Agentic AI Architecture

• Architect end-to-end GenAI-first and Agentic AI solutions on AWS using:
• Amazon Bedrock
• Amazon AgentCore
• Strands SDK Multi-Agents
• AWS Agents for Bedrock
• Knowledge Bases for Bedrock
• Guardrails for Bedrock
• Amazon SageMaker for model lifecycle & fine‑tuning
• Design multi-agent systems supporting planning, reasoning, tool invocation, memory stores, and multi-step workflows.
• Develop high-performance RAG architectures using:
• Amazon OpenSearch Serverless
• Kendra
• Aurora + pgvector
• Redis Enterprise
• Implement secure prompt flows, tool integrations, embeddings pipelines, and evaluation frameworks optimized for AWS.

• Build Python-based microservices (FastAPI/Django) integrated with AWS AI stack.
• Design scalable architectures using AWS-native components:
• Lambda, Step Functions, EventBridge, SQS, DynamoDB, API Gateway, ECS/EKS
• Implement enterprise-class LLMOps using:
• Amazon SageMaker Pipelines
• AWS CodePipeline / CodeBuild
• CloudWatch / X-Ray observability
• Establish standards for:
• Agent governance & safety
• Secure model invocation
• Guardrails & content filters
• Latency & cost optimization patterns

• Ensure compliance with enterprise security standards using: 
• IAM, KMS, VPC endpoints, PrivateLink, CloudTrail
• Optimize AI workloads for cost, performance, and scalability, including model caching, selective batching, and autoscaling strategies.
• Conduct architecture reviews, threat modeling, and performance benchmarking.

• Assess new AWS AI services, foundation models, agent frameworks, and vector DBs.
• Create internal accelerators, reusable patterns, and AWS-focused reference architectures for:
• Multi-agent orchestration
• RAG 2.0 / context enrichment
• Federated retrieval
• Enterprise tool integration
• Lead PoCs, prototypes, and technical spikes to validate emerging AWS GenAI capabilities.

• Mentor engineering teams on AWS GenAI patterns, LLMOps, cloud-native development, and distributed AI architectures.
• Provide technical direction, best practices, and deep architectural guidance across delivery teams.
• Create internal documentation, architecture blueprints, and engineering playbooks.

Required Skills & Qualifications

• AWS Certified Associate/Professional Solutions Architect.

Experience Level

Senior Level