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Wrapbook is an AI-powered production finance platform trusted by Netflix, Paramount, and other major studios. The company is building systems that help finance teams manage payroll, spend, and accounting through AI automation.
You'll join the Agentic Systems team to design and build production-grade AI agents that automate workflows across Wrapbook's internal operations. Working directly with teams in Marketing, Sales, Support, Operations, and Finance, you'll identify high-leverage processes and ship agents that meaningfully reduce manual work.
Key responsibilities include:
- Design and build production-grade AI agents using LangGraph that automate multi-step workflows for internal teams
- Deploy and scale agents on Amazon Bedrock AgentCore, managing runtime, memory, identity, and gateway capabilities while tracking costs and efficiency
- Partner with non-technical teams to understand workflows, extract requirements, and translate them into agent-driven solutions
- Integrate agents with Wrapbook's internal systems, APIs, and third-party tools to enable real actions
- Build evaluation, observability, and guardrail frameworks to measure agent quality and maintain human oversight
- Establish reusable patterns, shared tools, and best practices for the team to ship agents consistently
- Own agents end-to-end from prototype to production, measuring impact and iterating based on usage data
- Drive adoption through documentation, training, and enablement so teams understand and trust the agents
This role offers the opportunity to shape how a 400+ person company operates on AI, with visible daily impact and influence over agent-building standards and patterns.
Requirements:
- 6+ years of back-end development experience with Python, TypeScript/Node.js, or Java, with a track record of building systems for security, scalability, availability, and performance
- Hands-on experience building and shipping LLM-powered agents or workflows (Claude, GPT, Llama, Mistral, etc.), including prompting, tool use, and structured outputs; ability to discuss a built agent in detail
- Production experience with at least one agent or LLM framework (LangGraph, LangChain, LlamaIndex, AutoGen) and solid understanding of AI architectures (RAG, reranking, multi-agent orchestration); LangGraph experience is a plus
- Security-first mindset with attention to data access, permissions, and failure modes, especially for agents taking real actions
- Strong product sense and communication skills to work directly with non-technical teams
- Comfort with ambiguity and ownership mentality to move from loosely defined problems to production independently
- Nice to have: production AWS experience and familiarity with Amazon Bedrock AgentCore
