Jobs at Robots & Pencils

The Staff Full Stack Engineer will design and deliver complex enterprise integration platforms, focusing on full-stack applications and AWS data pipelines while mentoring junior engineers.

The Staff Full Stack Engineer will lead complex platform integrations, define technical strategies, build scalable systems, mentor junior engineers, and communicate architectural decisions effectively.

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.

Responsible for client P&L, building C-suite relationships, winning high-value deals, and ensuring client success while mentoring others.

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 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.

As a Senior Fullstack Engineer, you will develop and maintain applications, integrating backend services and APIs, and ensure system reliability and performance.

Develop and maintain backend services using Node.js and support fullstack applications, collaborating on system reliability and optimization in a cross-functional team.

Lead end-to-end GenAI and agentic AI product initiatives for enterprise clients: define strategy and roadmap, run discovery and experiments, prototype and productionize agents, establish evaluation metrics and guardrails, manage deliveries, and partner with stakeholders and AWS to ensure scalable, secure deployments.

As a Staff AI Engineer, you will develop backend services, integrate APIs, and optimize existing systems within a complex AI platform environment, collaborating with cross-functional teams and ensuring high reliability and performance.

The Staff AI Engineer will develop and maintain backend services, support workflows, optimize performance, troubleshoot production issues, and collaborate on feature development.

The Staff AI Engineer will develop backend services, integrate APIs, optimize performance, and ensure system reliability in cloud-native environments.

Seeking a Senior Data Architect who designs and deploys predictive models, analyzes complex datasets, and collaborates with cross-functional teams to drive data-driven product innovation.

Lead design and delivery of cloud-native infrastructure, CI/CD, Kubernetes, and platform tooling. Operate AI/ML platform infrastructure (model serving, GPU orchestration, LLM gateways, vector stores), implement IaC and DevSecOps, drive observability and cost/security practices, respond to incidents, and mentor junior engineers while collaborating across engineering, QA, and product.

Lead AI strategy engagements, manage complex client relationships, drive discovery, and deliver actionable plans to increase business effectiveness with AI solutions.

Lead AI architecture and technical strategy across the full lifecycle: design, build, and operate LLM-powered systems and scalable ML platforms. Implement event-driven, distributed systems, integrate AI with enterprise backends, ensure reliability/security/monitoring, and mentor engineers while shaping organizational AI standards and roadmaps.

The Principal Architect will lead the design and delivery of complex multi-domain systems, focusing on cloud, data, and AI. Responsibilities include defining technical strategy, mentoring engineers, and ensuring compliance and performance of architectures.

The Staff Data Engineer will lead data platform initiatives, define data strategy, build scalable data pipelines, and mentor junior engineers, emphasizing performance and governance.

The Principal Data Scientist will design scalable approaches for decision-making, apply diverse data science techniques, build data queries, analyze trends, and implement machine learning models. Collaboration with stakeholders and mentoring junior data scientists are key aspects of the role.