Jobs at Robots & Pencils

Build and operate production machine learning training systems on Amazon SageMaker using AWS Trainium. The role focuses on optimizing PyTorch code for Trainium hardware, understanding NeuronCore compilation, diagnosing device-level issues, tuning distributed training for cost and throughput, and delivering production pipelines. The engineer will collaborate directly with client and internal teams in a forward-deployed engineering environment.

Lead product vision and strategy for complex, high-stakes digital products in client engagements. Serve as the senior product advisor to executives, define operating models and delivery standards, guide discovery and roadmapping, resolve complex product decisions, and establish success metrics. Mentor experienced product managers, influence engineering and design teams, support business development, and improve product management practices. Apply AI tools such as Claude to increase efficiency and strengthen research and product thinking.

Define product strategy, vision, roadmaps, success metrics, and delivery plans for complex client engagements. Lead discovery, prioritization, stakeholder alignment, executive communication, and cross-functional collaboration across engineering, design, delivery, and strategy. Build trusted client relationships, facilitate workshops, mentor PMs, establish delivery standards, and resolve complex product and technical challenges. Apply AI tools such as Claude to accelerate research, discovery, synthesis, and documentation.

Leads architecture and delivery of complex cloud, data, and AI/ML systems. Defines technical strategy, designs scalable multi-cloud solutions, establishes infrastructure and DevOps standards, and oversees data platforms, MLOps, model serving, and LLM applications. Partners with clients and leadership, makes high-stakes technical decisions, drives modernization and optimization, documents standards, mentors senior engineers, and evaluates emerging technologies while ensuring security, governance, compliance, reliability, and performance.

Lead architecture and delivery of complex cloud, data, and AI/ML systems. Define technical strategy, design scalable multi-cloud platforms, data pipelines, MLOps and LLM applications, and establish infrastructure, DevOps, security, governance, and observability standards. Partner with clients and leadership, resolve high-stakes integration challenges, mentor senior engineers, guide technology decisions, and lead cloud modernization initiatives.

Lead design and delivery of enterprise generative and agentic AI systems on AWS. Architect Bedrock-based RAG and multi-agent platforms, prototype in Python, ensure security, observability, IaC, and guide clients from discovery to production.