Staff AI Architect

🔥 2 hours ago

🇺🇸 United States – Remote

💵 $146.1k - $201.5k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

👻 Ghost score 6%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Robots & Pencils

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

💰 Venture Round on 2022-04

Artificial Intelligence • B2B • SaaS

Robots & Pencils is a digital innovation firm that specializes in developing digital strategies and products utilizing mobile, web, and frontier technologies to drive transformation for businesses. They focus on areas such as mobile development, product design, UX research, artificial intelligence, machine learning, and organizational change management. With a commitment to blending creativity with technology, they aim to unlock data insights and enhance product innovation, ultimately delivering excellent customer experiences and helping brands gain a competitive edge.

📋 Description

• Define AI system architecture and lead design across LLM applications, agentic systems, retrieval, and ML model serving for end-to-end engagements • Drive RAG and context-engineering strategy, including hybrid retrieval, reranking, chunking, and embedding model selection across vector stores • Lead multi-agent orchestration design using frameworks such as LangGraph, Amazon Bedrock Agents, or AgentCore • Own model serving and inference architecture on AWS, optimizing latency, throughput, and cost with streaming, caching, batching, and quantization • Define LLMOps and MLOps standards across engagements, including prompt versioning, evaluation pipelines, CI/CD, and feature stores • Drive evaluation, guardrails, and observability strategy, establishing offline and online evaluation, LLM-as-judge scoring, and tracing • Own responsible AI posture, including governance, PII and data isolation, prompt-injection defense, and grounding controls • Lead decisions on fine-tuning, prompting, RAG, and tool use while weighing accuracy, cost, and maintainability • Use AI-forward tools such as Claude and Cursor to ship higher-quality work at pace • Partner with leadership and clients on AI technical direction and translate business goals into architectural decisions • Communicate complex AI concepts and tradeoffs to engineering and non-engineering stakeholders • Collaborate with engineering, data, ML, and product teams • Develop and maintain AI architecture documentation, evaluation standards, and reusable patterns • Establish architectural standards and best practices across the team • Mentor junior and mid-level engineers • Act as a technical escalation point for complex architectural and integration challenges • Evaluate emerging technologies and recommend tools, frameworks, and patterns

🎯 Requirements

• 7+ years of professional software engineering experience • At least 3 years in AI/ML architecture or technical leadership roles • Deep expertise in LLM and agentic application architecture, including multi-agent orchestration and tool-calling patterns • Strong experience designing production RAG and retrieval systems, including hybrid retrieval, reranking, and vector store selection • Strong experience with model serving and inference optimization on AWS, including latency, throughput, and cost tuning • Deep understanding of LLMOps and MLOps, including eval pipelines, prompt versioning, CI/CD, and observability for AI workloads • Demonstrated experience with AI evaluation, guardrails, and tracing tooling • Strong judgment on fine-tuning versus prompting versus RAG tradeoffs for accuracy, cost, and maintainability • Expert software engineering background, with proficiency in Python and at least one other language (e.g., TypeScript, Java, Go) • Strong background in cloud-native architecture, including microservices, serverless, containerization, and event-driven systems • Strong understanding of responsible AI and governance, including data isolation, prompt-injection defense, and compliance • Demonstrated leadership and technical mentoring experience across a team • Demonstrable, day-to-day usage and expert knowledge of AI-forward tools such as Claude and Cursor • Excellent problem-solving skills and ability to navigate ambiguous technical and business challenges • AWS AI certifications, fine-tuning or model customization experience, or responsible AI experience is a plus • Successful completion of a background check may be required

🏖️ Benefits

• Paid time off • Medical insurance • Dental insurance • Vision insurance • 401(k)