Jobs at Robots & Pencils

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.

Lead design and delivery of enterprise generative and agentic AI systems on AWS. Architect scalable, secure Bedrock- and SageMaker-based platforms, validate via Python prototypes, enforce AWS Well-Architected and security best practices, mentor delivery teams, and drive business-aligned production deployments and reusable accelerators.

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.

Deploy and operate production GenAI agents, MCP servers, and ML prediction APIs in Azure and AWS environments. Responsibilities include containerization with Docker, CI/CD through GitHub Enterprise, Azure ML workspace and compute setup, access management, observability, troubleshooting, and deployment documentation. The engineer will collaborate with Data Scientists and ML Engineers, support enterprise client environments, and potentially build demand-prediction models. MLOps, data engineering, and consulting experience are preferred.

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.

Implement, deploy, and maintain production-grade AI/ML systems and pipelines. Contribute to model training, inference services, MLOps/LLMOps workflows, monitoring, and data ingestion. Collaborate with product and engineering teams to operationalize research prototypes, debug cross-layer issues, and deliver reliable, scalable AI features.

Design and build scalable backend services and integrations for mobile apps in AWS. Implement event-driven architectures, authentication, API integrations (MuleSoft, GraphQL), CI/CD, and collaborate with architects, product owners, and mobile teams while using AI-assisted development tools.

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 architecture and delivery for cloud, data, and AI/ML systems. Define technical strategy, design scalable cloud-native and data platforms, build MLOps and model serving, establish IaC/CI-CD standards, ensure security/compliance, mentor engineers, and act as technical escalation point for complex integrations and migrations.

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 deploy scalable data science and generative AI solutions: acquire and ETL data from S3/RedShift/Spark, analyze data quality, build/validate models (ML, NLP, networks), deploy models to production, and mentor teams while collaborating with stakeholders and engineering.

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.

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

Lead testing and quality efforts for AI/ML systems and integrated platforms. Design scalable automation frameworks, validate ML models and LLM outputs, integrate tests into CI/CD, monitor production model quality, and mentor junior engineers while collaborating across engineering, DevOps, and product teams.

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.