Staff AI Engineer building production agentic AI and GenAI systems at Robots and Pencils. Designing RAG pipelines, AWS architectures, evaluations, and reliable full - stack integrations.
About the role
- Staff Agentic AI Engineer building Netomi’s enterprise customer-experience automation platform. Designing scalable LLM agents, retrieval systems, evaluations, and Python services for complex business workflows.
Responsibilities
- Design, build, and improve production-grade AI agentic systems for Netomi’s core platform
- Architect agent workflows involving reasoning, tool use, retrieval, guardrails, escalation paths, and performance monitoring
- Evaluate Deep Agent, Claude Agent, OpenAI Agent, LangGraph, and other emerging agent orchestration patterns and frameworks for new use cases
- Build and maintain LLM evaluation systems, including LLM-as-judge workflows, regression evaluations, guardrail testing, quality metrics, and production behavior analysis
- Diagnose agent performance issues across prompts, tool selection, retrieval quality, latency, cost, task completion, and failure modes
- Design and implement RAG and embedding-based capabilities for enterprise knowledge access and automation workflows
- Build scalable Python services and platform components deployed in AWS cloud environments
- Partner with product, platform, and engineering teams to translate emerging agentic AI capabilities into reliable platform features
- Establish engineering best practices for continuous optimization of agentic systems
- Stay current with advances in LLMs, agent architectures, AI coding tools, evaluation methodologies, retrieval systems, and enterprise automation
Requirements
- Bachelor’s Degree or higher in a quantitative field such as Statistics, Computer Science, Engineering, or Mathematics
- 5–7+ years of experience in AI/ML engineering, applied machine learning, natural language processing, and/or AI systems development
- 2+ years of hands-on experience building production LLM or AI agent systems
- Demonstrated experience building agents used in production by external customers or enterprise/business users
- Hands-on experience with LangGraph, LangChain, or related agent orchestration frameworks
- Experience turning messy, unstructured source material into validated structured output using schemas, ontologies, or data contracts with entity resolution, disambiguation, and conflict resolution
- Strong Python engineering skills and experience building scalable production software systems
- Experience designing agent architectures involving tool use, reasoning flows, retrieval, memory, guardrails, and workflow orchestration
- Experience developing AI evaluation systems, including LLM-as-judge, guardrail evaluation, regression testing, and production quality measurement
- Strong understanding of RAG, embeddings, retrieval quality, and knowledge-grounded generation
- Experience deploying or operating systems in AWS cloud environments
- Daily use of AI coding tools such as Codex, Claude Code, Cursor, or similar tools in software development workflows
- Strong engineering judgment, ability to work independently, and comfort operating as a senior individual contributor on ambiguous technical problems
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