Principal AI Engineering Architect

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Gugu Robotics

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🚘 Automotive

🎖️ Defense

🏥 Healthcare

Automotive • Defense • Healthcare

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

• Define technical strategy and lead architectural design across cloud, data, and AI/ML systems for end-to-end engagements, owning architecture decisions and driving solutions from research through production at scale • Architect and ship production-grade multi-agent agentic AI systems, including agent orchestration, tool use, memory, and inter-agent communication patterns • Design and build with Amazon Bedrock AgentCore and complementary AWS GenAI services to deploy, scale, and operate agentic workloads securely in production • Architect scalable cloud-native solutions with a strong bias toward AWS, including multi-cloud and hybrid strategies where needed (AWS primary, with Azure, GCP, Kubernetes as secondary) • Design data architectures including warehouses, data lakes, and pipelines for batch and streaming workloads (e.g., Snowflake, Redshift, BigQuery, Spark, Kafka) • Design AI/ML systems including model serving, MLOps pipelines, feature stores, and LLM-based applications (e.g., SageMaker, Bedrock, AgentCore, Vertex AI, MLflow, Hugging Face) • Build and evolve scalable ML platforms, pipelines, and infrastructure that support reliable, repeatable model development and deployment across teams • Define infrastructure as code, CI/CD, and DevOps standards across engagements (e.g., Terraform, CloudFormation, GitHub Actions) • Drive performance, scalability, cost, and reliability optimization across deployed systems • Ensure architecture meets security, governance, and compliance requirements (e.g., GDPR, HIPAA, SOC2) • Lead cloud migrations and platform modernization initiatives • Set the standard for AI-forward engineering, using tools like Claude and Cursor with sophistication and helping the team adopt them effectively

🎯 Requirements

• 8+ years of software engineering experience, with at least 5 years in technical leadership roles and 4+ years focused on AI/ML systems in production • Expert software engineering background (Python or similar) with strong design sensibilities for scalable, maintainable systems • Deep, hands-on expertise designing and shipping production multi-agent agentic AI systems, including agent orchestration, planning, tool use, and multi-agent coordination patterns • Deep expertise with AWS, including in-depth knowledge of AWS GenAI offerings and hands-on experience with Amazon Bedrock AgentCore; broader multi-cloud experience (Azure, GCP) is a plus • Strong background in microservices, serverless, containers, and event-driven systems (e.g., Kubernetes, Docker, Lambda, EventBridge) • Proficiency with infrastructure as code and CI/CD (e.g., Terraform, CloudFormation, Pulumi, GitHub Actions) • Strong data architecture expertise across relational, NoSQL, and big data systems (e.g., PostgreSQL, MongoDB, Snowflake, BigQuery, Spark, Kafka) • Hands-on experience with data modeling, ETL/ELT pipelines, and orchestration (e.g., Airflow, Prefect, dbt) • Mastery of AI frameworks and orchestration tools for building agentic systems (e.g., LangChain, LangGraph, AgentCore, CrewAI, AutoGen, or equivalents) • Strong experience designing AI/ML systems for production, including LLMs, MLOps, and model serving (e.g., SageMaker, Bedrock, Vertex AI, MLflow, Hugging Face, PyTorch, TensorFlow) • Strong experience with evaluation frameworks and observability tools for LLM and agentic apps, including building these capabilities where they don't yet exist • Deep understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling • Extensive experience building RAG pipelines: chunking strategies, embedding models, vector databases, and advanced retrieval techniques • API design experience, including architecting and integrating with internal and third-party services at scale • Advanced cost optimization expertise: token economics, caching strategies, model routing, quantization • Solid understanding of networking, security, identity, and access management in cloud environments • Experience with governance, compliance, and observability frameworks • Track record of senior technical leadership and mentoring experienced engineers • Strong stakeholder communication skills, with the ability to translate technical depth across audiences • Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude Code and Cursor • Multi-cloud architecture experience, AI ethics or responsible AI experience, or enterprise architecture certifications (e.g., TOGAF, AWS/Azure/GCP) is a plus.