Principal Architect

We’re looking for a Principal Architect to lead the design and delivery of complex, multi-domain systems spanning cloud, data, and AI. This role is ideal for a deeply experienced engineer who owns the hardest architectural challenges, sets technical direction, and serves as the senior technical voice on the engagements they support. In this role, you will operate as the senior technical authority on a cross-functional team, defining architecture across cloud infrastructure, data platforms, and AI/ML workloads. You’ll partner closely with leadership and clients on technical strategy, mentor experienced engineers, and own high-stakes decisions that shape the long-term success of the systems you build. Why This Role Matters At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate. Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on. What You’ll Do Craft & Delivery Define technical strategy and lead architectural design across cloud, data, and AI/ML systems for end-to-end engagements Architect scalable cloud-native solutions, including multi-cloud and hybrid strategies (e.g., AWS, Azure, GCP, Kubernetes) Design data architectures including warehouses, data lakes, and pipelines for batch and streaming workloads (e.g., Snowflake, Redshift, BigQuery, Spark, Kafka) Design AI/ML systems including model serving, MLOps pipelines, feature stores, and LLM-based applications (e.g., SageMaker, Vertex AI, MLflow, Hugging Face) Define infrastructure as code, CI/CD, and DevOps standards across engagements (e.g., Terraform, CloudFormation, GitHub Actions) Drive performance, scalability, cost, and reliability optimization across deployed systems Ensure architecture meets security, governance, and compliance requirements (e.g., GDPR, HIPAA, SOC2) Lead cloud migrations and platform modernization initiatives Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace Collaboration & Communication Partner with senior leadership and clients as the principal technical voice on strategy and direction Communicate complex technical concepts clearly to engineering and non-engineering stakeholders alike Engage closely with engineering, data, AI, and product teams to align architecture with broader business priorities Develop and maintain architecture documentation, standards, and guidelines Leadership & Influence Define and champion architectural standards and best practices on the engagements you support Mentor experienced engineers and architects, helping them grow their technical judgment and impact Own the most difficult architectural and integration challenges, serving as the senior technical decision-maker Evaluate emerging technologies and recommend tools, frameworks, and patterns that improve architecture over time What You’ll Bring 8+ years of experience in software engineering, with at least 5 years in technical leadership roles Deep expertise in cloud platforms and cloud-native architectures (e.g., AWS, Azure, GCP) Strong background in microservices, serverless, containers, and event-driven systems (e.g., Kubernetes, Docker, Lambda, EventBridge) Proficiency with infrastructure as code and CI/CD (e.g., Terraform, CloudFormation, Pulumi, GitHub Actions) Strong data architecture expertise across relational, NoSQL, and big data systems (e.g., PostgreSQL, MongoDB, Snowflake, BigQuery, Spark, Kafka) Hands-on experience with data modeling, ETL/ELT pipelines, and orchestration (e.g., Airflow, Prefect, dbt) Strong experience designing AI/ML systems for production, including LLMs, MLOps, and model serving (e.g., SageMaker, Vertex AI, MLflow, Hugging Face, PyTorch, TensorFlow) Solid understanding of networking, security, identity, and access management in cloud environments Experience with governance, compliance, and observability frameworks Strong software engineering skills (Python, APIs, containerization) Track record of senior technical leadership and mentoring experienced engineers Strong stakeholder communication skills, with the ability to translate technical depth across audiences Demonstrable usage of AI-forward tools such as Claude and Cursor Multi-cloud architecture experience, AI ethics or responsible AI experience, or enterprise architecture certifications (e.g., TOGAF, AWS/Azure/GCP) is a plus