Jobs at Robots & Pencils

Lead development of a production-grade evaluation framework for planner-executor agents. Build user simulation, isolated experiment execution, grading, statistical analysis, tracing, optimization-lever plugins, and a locally hosted dashboard. Run experiments comparing models and inference strategies, quantify quality, latency, and cost tradeoffs, generate evidence-backed insights, and deliver client recommendations. Partner with engineers and business stakeholders, communicate findings, establish evaluation standards, and mentor others.

Designs and delivers cloud-native applications on AWS, including microservices, serverless functions, APIs, event-driven systems, infrastructure as code, and CI/CD pipelines. The role emphasizes scalability, resilience, observability, security, and cost optimization, while integrating AI and LLM services using RAG and inference workflows. Responsibilities include architecture documentation, technical collaboration, code and design reviews, end-to-end ownership, and mentoring junior engineers.

Leads large-scale AI, digital, and cloud transformation programs from strategy through launch and realized business value. The role coordinates concurrent Agile teams, technical direction, architecture discussions, AI lifecycle governance, risk management, KPIs, stakeholder communication, staffing, and executive decision-making. It requires translating business goals into technical plans, managing complex dependencies and trade-offs, mentoring delivery leaders, and shaping delivery practices while partnering with clients on growth opportunities.

Lead large-scale AI, digital, and cloud transformation programs from strategy through launch and realized business value. Manage multiple Agile teams, workstreams, dependencies, governance, KPIs, budgets, risks, and executive stakeholder alignment. Translate business needs into technical requirements, facilitate architecture discussions, establish AI lifecycle and evaluation standards, and guide decisions involving model risk, observability, and agentic solutions. Mentor delivery managers, support staffing and hiring decisions, and contribute to client expansion opportunities and delivery practice improvements.

Leads architecture and delivery of production-grade AI, multi-agent, cloud, data, and ML systems. Defines AWS-centered technical strategy, builds agentic platforms, designs data pipelines and MLOps infrastructure, and establishes DevOps, security, governance, observability, and cost standards. Serves as the senior technical authority for clients and cross-functional teams, mentors engineers, evaluates emerging technologies, and drives complex solutions from research through production.

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.

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 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.