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Robots & Pencils
Robots & Pencils
6 open remote positions
Robots & Pencils is an applied AI engineering firm that designs and ships AI co-workers integrated into enterprise operations. Founded in 2009 with delivery centers across North America, Eastern Europe, and Latin America, the company is smaller, faster, and more senior by design, with teams averaging 15+ years of experience.
Salary Distribution
5 of 6 jobs
Benefits Overview
5 of 6 jobs
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Open Positions
Lead end-to-end delivery of complex, multi-phase AI engagements, owning execution from kickoff through release. Facilitate sprint planning, backlog refinement, and delivery execution across cross-functional onshore and offshore teams. Serve as the primary delivery partner to clients, managing risks, KPIs, and production readiness.
Agile
Scrum
Jira
AI/ML
Cloud-native
Design, deploy, and optimize data and AI/ML systems on AWS end-to-end. Maintain and evolve production platforms, monitoring for drift and improving reliability. Partner with AWS Professional Services and client teams to align data and AI architecture with business goals.
Python
SQL
AWS
Data Engineering
Observability
Build and ship features of AI/ML and LLM-powered systems with guidance from senior engineers. Implement and maintain AI/ML and AI agent pipelines from data ingestion through model deployment. Contribute to LLM-powered features such as prompts, evaluations, retrieval, and tool integrations, while documenting experiments clearly.
Python
AWS
LLM
Machine Learning
Docker
Design, implement, and deploy ML/AI models end-to-end, including data pipelines, training workflows, and production optimization. Collaborate with product, engineering, and data teams to align AI work with business goals and translate technical tradeoffs. Contribute to AI architecture decisions and raise engineering practices, using AI-forward coding tools like Claude and Cursor.
Python
AWS
Generative AI
RAG
Docker
Define DevOps strategy and lead infrastructure architecture across multi-environment, multi-region cloud systems. Architect and own scalable Kubernetes platforms, infrastructure as code, and DevSecOps implementation. Drive platform reliability, performance SLAs, cost optimization, and lead complex migrations and AI/ML platform infrastructure.
Kubernetes
Infrastructure As Code
DevSecOps
Python
Go
Contribute to architectural design across cloud, data, and AI/ML systems. Build cloud-native solutions including microservices, serverless, and containerized workloads. Implement infrastructure as code, CI/CD pipelines, and data architectures.
Python
TypeScript
AWS
Infrastructure As Code
CI/CD