• Design, implement, and deploy ML/AI models end-to-end • Maintain and evolve AI systems in production • Bring an AI-forward coding mindset • Partner closely with product, engineering, and data teams • Translate technical tradeoffs into terms non-specialists can act on • Participate actively in code reviews and design discussions • Contribute to AI architecture decisions • Take ownership of meaningful work end-to-end • Raise the bar on engineering practices by supporting junior engineers

• Work directly with key stakeholders in a consultative manner to identify pain points and start building solutions to simplify manual and redundant workflows. • Write the production code — this isn't a strategy role. • Build agents to automate grind. • Partner with function heads to design, test, and deploy AI-driven agents and workflow automations. • Own evals, observability, guardrails, and the 'is this thing actually working' layer. • Use AI coding assistants (e.g. Claude, Replit, Vercel, etc.), low/no-code platforms, and workflow automation tools to rapidly build and ship MVPs. • Own cloud infrastructure, CI/CD, and operational reliability for what you ship. • Lead vendor evaluations, negotiate modular solutions, and ensure clean integration with our data and AI platforms.

• Build and extend multi-agent systems and agentic workflows using frameworks such as AWS Agent Core and AWS Bedrock Flows (or equivalent orchestration tools). • Develop and integrate Retrieval-Augmented Generation (RAG) pipelines for internal tools. • Implement LLM-powered chatbots, assistants, and autonomous agents tailored to specific business use cases. • Collaborate closely with the Team Lead to understand requirements and translate them into reliable, scalable implementations. • Take existing proof-of-concept or in-progress AI systems and harden them to production-grade standards. • Pipeline AI components together within the AWS and Databricks ecosystem, ensuring reliable end-to-end data and model workflows. • Apply best practices in observability, logging, and monitoring for deployed AI systems. • Contribute to CI/CD processes for model and prompt deployment where applicable. • Mentor and support other engineers within AI. • Communicate progress, blockers, and technical decisions clearly to both technical and non-technical stakeholders. • Participate in technical discussions and contribute to architectural decisions for AI systems.

Role Description 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. - 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. - 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. - 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. Qualifications - 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. - Strong problem-solving skills and the ability to navigate ambiguous technical challenges with sound judgment. Requirements - A doer who sees something broken and fixes it. - A fast learner who is curious and keeps learning. - Direct in a way that improves work quality. - Obsessed with craft and detail. - Built for ownership and accountability. - All in for client success and resourceful under constraints. - Glad to collaborate with experienced team members. Benefits - Comprehensive package of benefits including paid time off. - Medical/dental/vision insurance. - 401(k) to eligible employees. Company Description 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. Founded in 2009, we are smaller, faster, and more senior by design, with teams averaging 15+ years of experience.