Senior AI Engineer

Company Overview 

Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients. We're all in on AWS, combining deep UX capability with senior engineering talent to get AI into production fast and keep it there. 
We’ve earned the trust of leaders across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing and more, and earned a reputation as the nimble alternative to traditional global systems integrators. Founded in 2009, with delivery centers in Canada, the United States, Eastern Europe, and Latin America, we are smaller, faster, and more senior by design. Our teams average 15+ years of experience. We move fast, sweat the details, and build things that actually ship. 

Position Overview 

We’re looking for a Senior AI Engineer to design, build, and deliver production AI/ML systems. This role is ideal for an engineer with several years of experience who can confidently own features end-to-end, contribute to architectural decisions, and bring strong technical judgment to the problems they take on. 

In this role, you will work as a key contributor on a cross-functional team, designing and implementing models, building the data pipelines and training workflows around them, and deploying systems to production environments. You’ll be joining real, in-flight work where reliability, performance, and scalability matter. You’ll collaborate with experienced engineers to enhance existing systems, deliver new capabilities, and contribute to the technical decisions that shape how our AI work scales over time. 

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 

• Design, implement, and deploy ML/AI models end-to-end, from concept through production, including data pipelines, training workflows, and optimization for performance, accuracy, and efficiency 

• Maintain and evolve AI systems in production, monitoring for drift, debugging issues, and driving ongoing improvements to reliability and scalability 

• Bring an AI-forward coding mindset to your daily work, using tools like Claude and Cursor to ship higher-quality work at pace 

Collaboration & Communication 

• Partner closely with product, engineering, and data teams to align AI work with broader product and business goals 

• Translate technical tradeoffs, model behavior, and constraints into terms non-specialists can act on 

• Participate actively in code reviews and design discussions, raising concerns and offering constructive feedback 

Leadership & Influence 

• Contribute to AI architecture decisions with thoughtful perspective on tradeoffs and long-term implications 

• Take ownership of meaningful work end-to-end, including the unglamorous parts of getting AI into production 

• Raise the bar on engineering practices through your own work and by supporting more junior engineers when opportunities arise 

What You’ll Bring 

• 4+ years professional software engineering experience, with 2+ years focused on AI/ML systems in production and hands-on experience with generative AI development 

• Strong software engineering background (Python or similar) 

• Working knowledge of cloud platforms, preferably with in-depth understanding of AWS services and AWS GenAI offerings 

• Proven ability to design and ship agentic systems 

• Experience with AI frameworks and orchestration tools 

• Experience with evaluation frameworks, and observability tools for LLM apps 

• Understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling 

• Hands-on experience building RAG pipelines: chunking strategies, embedding models, vector databases 

• API development experience, including designing and integrating with internal and third-party services 

• Cost optimization expertise: token economics, caching strategies, model routing, quantization 

• Working knowledge of Docker and Kubernetes for containerized deployments 

• Demonstrable, day-to-day usage and knowledge of AI-forward coding tools such as Claude Code and Cursor