VP of Solutions Architect – AI

Gugu Robotics

AWS AI Solutions Architect responsible for designing enterprise-scale AI systems and solutions using AWS. Collaborating with strategic clients and mentoring engineering teams for impactful AI implementations.

Posted 7/17/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AWS AI architecture, focusing on generative and agentic AI system design, while ensuring adherence to AWS security best practices and operational excellence. Proficient in leading enterprise-scale transformations and mentoring teams on AWS service integration and MLOps.

Highest-signal resume keywords

AWS AI ArchitectureAmazon BedrockSageMakerInfrastructure as CodeAWS Professional Certifications

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonAWS SDKsDistributed SystemsEvent-Driven ArchitecturesServerless PatternsRAG ArchitecturesModel Fine-TuningObservability StrategiesMulti-Agent OrchestrationCloudFormation

Soft Skills

Exceptional Communication Skills

Tools & Technologies

AWS Strands AgentsAgentCore GatewayAWS LambdaAWS Step FunctionsAPI GatewayDynamoDBAuroraOpenSearchCloudWatchCloudTrail

Certifications & Qualifications

AWS Solutions Architect – ProfessionalAWS DevOps Engineer – Professional

Industry Keywords

MLOpsGovernanceResponsible AIComplianceOperational Complexity

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsDynamoDBPythonTerraform

About the role

Key responsibilities & impact

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.
Accelerate time-to-value through reusable AWS accelerators, Infrastructure as Code (CloudFormation/Terraform/CDK), and CI/CD automation.
Continuously evaluate emerging AWS AI capabilities (Nova Forge, Nova 2 Sonic, Bedrock updates, and new AgentCore capabilities).
Provide architectural oversight to Forward Deployed Engineers and AWS delivery teams.
Establish best practices for MLOps on AWS including model lifecycle management, monitoring, and observability using SageMaker, CloudWatch, CloudTrail, and AWS Config.
Define governance, responsible AI guardrails, Bedrock Guardrails configuration, and security controls for enterprise environments.
Mentor engineers on AWS AI service integration, distributed systems design, and secure multi-account strategies.
Make principled tradeoffs under constraints related to privacy, compliance (SOC2, HIPAA, GDPR), cost, and operational complexity.
Partner with internal product, engineering, research, and customer success teams to evolve AWS-based AI offerings.
Contribute AWS reference architectures and reusable infrastructure modules to internal accelerators.
Support pre-sales engagements including architecture workshops, AWS migration strategy, and solution scoping.
Collaborate across distributed teams and client stakeholders across North America.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
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

Comp & perks

Professional development opportunities