The Future is Now; Beyond Boundaries, Beyond Imagination
Solutions Architect – AI
Location
United States
Posted
1 day ago
Salary
0
Seniority
Lead
Job Description
Solutions Architect – AI
Gugu Robotics
• Serve as the primary AWS AI architecture partner for strategic clients, driving generative and agentic AI system design from discovery through production. • Lead architecture design using Amazon Bedrock (including foundation models and custom models), Bedrock AgentCore, AWS Strands Agents, and AWS AgentCore Gateway. • Design advanced RAG, Agentic RAG, and multi-agent orchestration architectures leveraging AWS-native services such as Lambda, Step Functions, API Gateway, DynamoDB, Aurora (pgvector), and OpenSearch. • Produce AWS reference architectures, architecture decision records (ADRs), and implementation roadmaps aligned to business objectives. • Validate feasibility through hands-on prototyping in Python using Bedrock SDKs, SageMaker, and serverless services. • Ensure architectures follow AWS security best practices (IAM, KMS, VPC, PrivateLink) and cost optimization principles. • Own architectural integrity from concept through production deployment on AWS. • Align solutions with AWS Well-Architected Framework pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. • Guide clients through tradeoff decisions across model selection (Bedrock FMs vs custom SageMaker models), latency, cost, governance, and compliance. • Continuously evaluate emerging AWS AI capabilities (Nova Forge, Nova 2 Sonic, Bedrock updates, and new AgentCore capabilities).
Job Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
- 7–10+ years of experience in software engineering or cloud architecture with deep AWS ownership.
- Deep expertise in Amazon Bedrock, Bedrock AgentCore, AWS Strands Agents, AgentCore Gateway, and related AWS AI services.
- Strong familiarity with SageMaker (training, deployment, pipelines), deep learning fundamentals, and model fine-tuning strategies.
- Experience architecting RAG, multi-agent, and orchestration systems using AWS-native services.
- Strong knowledge of distributed systems, event-driven architectures, and serverless patterns.
- Proficiency with Infrastructure as Code (AWS CDK, CloudFormation, Terraform).
- Hands-on development capability in Python and AWS SDKs.
- Experience implementing observability and monitoring strategies in AWS environments.
- Proven success leading enterprise-scale AWS transformations.
- Exceptional communication skills for both technical and executive audiences.
- AWS Professional Certifications highly preferred (AWS Solutions Architect – Professional, AWS DevOps Engineer – Professional).
Benefits
- Health insurance
- Professional development opportunities
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