Jobs at Robots & Pencils

Lead platform engineering strategy across multi-environment and multi-region cloud systems. Architect Kubernetes and container platforms, establish infrastructure-as-code standards, and implement DevSecOps, security, compliance, reliability, observability, and cost optimization practices. Lead cloud migrations and AI/ML infrastructure initiatives involving model serving, GPU orchestration, LLM gateways, vector stores, and CI/CD. Mentor engineers, guide architecture decisions, communicate with stakeholders, and serve as a technical escalation point.

Lead delivery and growth for assigned enterprise accounts, owning strategy, program operations, P&L, and client relationships. Drive expansion and new-logo pursuits, coach delivery teams, contribute reusable IP, and ensure delivery of production-ready applied-AI solutions on schedule and on margin.

Designs and delivers complex cloud, data, and AI/ML systems. Responsibilities include building cloud-native microservices, serverless and containerized workloads; implementing infrastructure as code, CI/CD, monitoring, and observability; contributing to data platforms and MLOps; and integrating LLM capabilities. The role collaborates with engineering, data, AI, and product teams, documents architecture, participates in design reviews, establishes best practices, and mentors junior engineers.

Leads end-to-end architecture for complex cloud, data, and AI/ML systems. Defines technical strategy, designs scalable multi-cloud and hybrid solutions, establishes infrastructure-as-code and DevOps standards, drives migrations and modernization, and optimizes performance, cost, security, and reliability. Partners with clients and leadership, documents architecture, mentors engineers, evaluates emerging technologies, and serves as a technical escalation point for complex integration challenges.

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.