Jobs at Robots and Pencils

• Design, implement, and deploy data and AI/ML systems on AWS end-to-end, from concept through production, including data lake pipelines, observability instrumentation, and optimization for performance, reliability, and cost
• Maintain and evolve platforms in production, monitoring for drift, debugging issues, and drivin...

• Define product strategy and vision for major client engagements, setting direction in alignment with client goals and business outcomes
• Own the product roadmap end-to-end, driving prioritization across business value, technical constraints, and delivery timelines

• Design and implement scalable data pipelines, taking ownership of features end-to-end
• Build and manage data warehouses and data lakes

• Build and ship features of AI/ML and LLM-powered systems with guidance from senior engineers, contributing to solutions that run in production
• Implement and maintain components of AI/ML and AI agent pipelines from data ingestion through model deployment, picking up the unglamorous parts as you grow

• Design, implement, and deploy ML/AI models end-to-end, from concept through production, including data pipelines, training workflows, and optimization for performance, accuracy, and efficiency
• Maintain and evolve AI systems in production, monitoring for drift, debugging issues, and driving ongoing improvements to reliability and scalability

• Define data architecture and platform strategy, leading design across pipelines, warehouses, and data lakes
• Build and optimize scalable data pipelines supporting batch and real-time processing

• Design and build agentic workflows — reasoning loops, tool/function calling, and orchestration across single- and multi-agent architectures — with clear judgment on which pattern fits the problem and which doesn't
• Build and maintain RAG pipelines: chunking strategy, embeddings, vector search (OpenSearch), re...

• Own end-to-end product delivery for complex AI and agentic AI engagements, from discovery and hypothesis framing through phased rollout and production readiness
• Define and maintain AI product roadmaps that connect agent capabilities to measurable enterprise business outcomes

• Define technical strategy and lead architectural design across cloud, data, and AI/ML systems for end-to-end engagements
• Architect scalable cloud-native solutions, including multi-cloud and hybrid strategies (e.g., AWS, Azure, GCP, Kubernetes)

• Define security architecture and engineering standards across web, API, and cloud-native systems, leading the hardening of complex services
• Lead threat modeling and security design reviews across applications and AI systems, setting how risk is identified and prioritized

• Contribute to architectural design across cloud, data, and AI/ML systems, taking ownership of meaningful components
• Build and integrate cloud-native solutions including microservices, serverless, and containerized workloads (e.g., AWS, Azure, GCP, Kubernetes, Docker)

• Train and operate models on Amazon SageMaker with AWS Trainium as the underlying compute
• Write and optimize PyTorch training code with a real understanding of how it compiles and executes on Trainium (NeuronCore architecture, compiler behavior, memory and throughput tradeoffs)

• Define DevOps strategy and lead infrastructure architecture across multi-environment, multi-region cloud systems
• Architect and own scalable Kubernetes platforms and containerized infrastructure at scale

• Define product strategy and vision for major client engagements, setting direction in alignment with client goals and business outcomes
• Own the product roadmap end-to-end, driving prioritization across business value, technical constraints, and delivery timelines

• Design end-to-end UX/UI deliverables from early exploration and concepting through high-fidelity execution
• Create wireframes, prototypes, and polished interface designs that balance usability, business goals, and technical constraints

• Define technical strategy and lead architectural design across cloud, data, and AI/ML systems for end-to-end engagements
• Architect scalable cloud-native solutions, including multi-cloud and hybrid strategies (e.g., AWS, Azure, GCP, Kubernetes)

• Lead the design and implementation of complex ML/AI systems end-to-end within client environments, owning architecture decisions and driving solutions from research through production at scale
• Build, deploy, and evolve scalable ML platforms, pipelines, and infrastructure that support reliable, repeatable model development and deployment — often within existing client constraints

We're looking for a Principal AI Engineering Architect to lead the design and delivery of complex, multi-domain systems spanning cloud, data, and AI — with deep, hands-on mastery of multi-agent agentic AI solutions. This role is ideal for a deeply experienced engineer who owns the hardest archite...

• Define mobile architecture and technical strategy across iOS and Android applications (e.g., Swift, Kotlin)
• Lead design and implementation of scalable mobile platforms and complex UI systems (e.g., SwiftUI, UIKit, Jetpack Compose)

• 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.