VP of Solutions Architect – AI

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Gugu Robotics

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🤖 Artificial Intelligence

🛍️ eCommerce

Artificial Intelligence • Robotics • eCommerce

Gugu Robotics is a pioneering startup based in West Africa, dedicated to harnessing the power of AI, robotics, and drone technology to create innovative solutions for various industries. Founded by visionary engineer Emmy Pencil, the company specializes in designing and building customized robotic systems, drones, and AI-enabled electric vehicles that address critical challenges across sectors such as agriculture, military, medical, and beyond. With a diverse team of experts, Gugu Robotics aims to redefine possibilities in automation and efficient energy solutions to shape the future of technology.

📋 Description

• 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

• 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

• Professional development opportunities