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.

Train and operate production machine learning models on Amazon SageMaker using AWS Trainium. Optimize PyTorch code for Trainium compilation, memory, throughput, and distributed training; diagnose hardware, compiler, device, data, and code issues; build cost-aware end-to-end training pipelines; and collaborate directly with client and internal engineering teams to deliver production workloads.

Lead platform engineering strategy across multi-environment and multi-region cloud systems. Architect Kubernetes platforms, infrastructure as code, CI/CD, DevSecOps, observability, and reliable production infrastructure. Lead cloud migrations, modernization, AI/ML platform infrastructure, model serving, GPU orchestration, and LLM platform capabilities. Mentor engineers, establish standards, conduct design reviews, communicate technical decisions, and serve as an escalation point for complex infrastructure challenges.

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.

Design and deliver complex cloud, data, and AI/ML systems. Build cloud-native microservices, serverless and containerized workloads; implement infrastructure as code, CI/CD, data pipelines, MLOps, model serving, LLM integrations, and observability. Collaborate across engineering, data, AI, and product teams, document architectural decisions, contribute to standards, and mentor junior engineers while taking increasing ownership of system architecture.

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.

Designs, builds, and scales production AI systems, including ML platforms, inference pipelines, agentic orchestration, LLMOps, RAG, and distributed infrastructure. The role owns architecture and technical strategy, operationalizes research prototypes, establishes evaluation and deployment practices, and ensures reliability, observability, security, and cost efficiency. It also mentors engineers, leads technical reviews, collaborates with product and executive stakeholders, and guides AI initiatives from experimentation through production.

Lead end-to-end product delivery for enterprise GenAI and agentic AI engagements: define roadmaps and agent behavior, run discovery, prototypes, evals and pilots, set metrics and guardrails, guide phased rollout, and communicate AI tradeoffs to senior stakeholders while mentoring junior PMs.

Design and lead scalable data architecture, lakes, warehouses, and batch or real-time pipelines. Establish governance, quality, compliance, monitoring, and deployment standards while modernizing platforms for performance, cost, and reliability. Build data flows for production AI/ML systems, including embeddings, vector stores, RAG preparation, feature stores, and training or inference data. Partner with engineering, analytics, AI, product, and leadership teams, make architectural decisions, and mentor engineers.

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 strategy and end-to-end UX/UI for complex, multi-platform client products. Own design system architecture and governance, direct UX research strategy, champion AI-assisted design workflows, and improve design operations. Partner with leadership, clients, engineers, and strategists; facilitate workshops and design sprints; mentor designers; establish quality standards; and contribute to marketing, business development, and growth of the design practice.

Lead design and delivery of complex full-stack, AI-integrated platforms. Define front-end architecture, own backend and API design, optimize databases, ensure scalability, reliability, and security, mentor engineers, and integrate LLMs and RAG-style AI services into production systems.

Lead platform engineering strategy across multi-environment cloud systems: design scalable Kubernetes platforms, own IaC and CI/CD standards, implement DevSecOps and observability, drive reliability/cost optimization, lead cloud migrations and AI/ML platform infrastructure (model serving, GPU orchestration, LLM gateway, vector stores), mentor engineers, and communicate infrastructure tradeoffs to stakeholders.

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.

Lead end-to-end delivery of production-grade GenAI and agentic solutions: frame problems, run discovery and prototyping, define agent behavior and evals, set success metrics and guardrails, and communicate tradeoffs to senior stakeholders while partnering with engineering to ship scalable AI co-workers.

Provide high-volume sourcing and recruiting coordination for global technical and delivery roles: proactively source candidates, conduct outreach, manage pipelines and metrics, schedule interviews across time zones, coordinate calendars, maintain tracking and documentation, and support offer logistics to ensure a smooth candidate experience.

Provide L2 IT support for remote macOS and Windows users across Latin America and North America: manage tickets, administer Microsoft 365/Entra ID, handle device enrollment via MDM, troubleshoot SSO/MFA and SaaS platforms, document resolutions, and escalate complex issues to senior sysadmin.

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.