Robots and Pencils
PrincipalAIEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Principal AI Engineer at Robots and Pencils. Skills: AI/ML systems, System architecture, LLM systems. Define technical direction. Drive technical direction”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
5+ years experience, Deep expertise, Broad systems thinking, High-stakes technical decisions, Experience with LLM systems, Experience with containerization, Experience with cloud-native AI architecture patterns
Nice to Have
Experience with other cloud platforms, Familiarity with SQL and NoSQL databases, Experience with workflow orchestration tools, Experience with asynchronous system operations, Prompt engineering, Function/tool calling, Multi-agent orchestration, RAG architectures, Vector databases, Embeddings, Streaming LLM responses, Docker, AI governance and compliance considerations
What You'll Do.
Define technical direction
Drive technical direction
Solve hardest problems
Set AI architecture standards
Lead implementation challenges
Solve integration problems
Partner with leadership
Make technical decisions
How You'll Work.
Team & Collaboration
Cross-functional team
Process & Methodology
Roadmap planning
Full Job Description
We’re looking for a Principal AI Engineer to define and drive the technical direction of our AI/ML systems. This role is ideal for a deeply experienced engineer who leads from the front — shaping architecture at the system level, solving the hardest problems, and raising the bar for how AI gets built and operated across the organization. In this role, you will work on a cross-functional team, setting AI architecture standards, leading complex system design and implementation challenges, and solving integration problems that require both deep expertise and broad systems thinking. You’ll partner closely with leadership to define the AI roadmap and make high-stakes technical decisions that shape how our AI work scales across clients and over time. Why This Role Matters At Robots working knowledge of other cloud platforms Familiarity with both SQL and NoSQL databases, including scalable design patterns Experience with workflow orchestration tools and asynchronous system operations Hands-on experience with LLM systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG architectures, vector databases, embeddings, and streaming LLM responses Experience with containerization (e.g., Docker) and cloud-native AI architecture patterns Exposure to AI governance and compliance considerations in production environments
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