[All remote jobs](https://jobicy.com/jobs.md)[![Wrapbook logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2024/03/4daf69c7-221.jpeg)](https://jobicy.com/company/wrapbook.md)[Wrapbook](https://jobicy.com/company/wrapbook.md) # Senior Software Engineer II, Applied AI Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/wrapbook.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md), [Canada](https://jobicy.com/job-region/canada.md)SalaryUSD 206k–283,500 / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished26 Oct 2026Apply before25 Nov 2026Listing views42Application actions4Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Wrapbook is hiring a senior backend-oriented AI engineer to build and operate production AI agents for internal business workflows. The role focuses on agent design with LangGraph, LLM integrations, tool use, evaluation frameworks, observability, security controls, and deployment on AWS/Amazon Bedrock AgentCore. The engineer will work directly with non-technical stakeholders across marketing, sales, support, operations, and finance to identify and automate high-impact processes. This is a high-ownership role requiring end-to-end delivery from ambiguous requirements and prototypes through production rollout, adoption, and iteration. Candidates must be authorized to work remotely from the United States or Canada. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior, production-focused applied AI role requiring substantial backend engineering experience plus demonstrated delivery of reliable LLM agents. The work combines ambiguous product discovery, security-sensitive integrations, evaluation, cloud operations, and cross-functional change management. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Highly competitive$244,750US market range (per year)$190k–$275k0$302.50k AI insightThe employer discloses a yearly base-pay range of $206,000–$283,500 USD, with a midpoint of $244,750. Estimated US market compensation for a senior applied AI/software engineer with production LLM-agent and AWS expertise is approximately $190,000–$275,000 USD per year; actual compensation may vary by location, scope, and total-equity structure. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[TypeScript](https://jobicy.com/jobs?search_keywords=TypeScript.md)[Node.js](https://jobicy.com/jobs?search_keywords=Node.js.md)[Java](https://jobicy.com/jobs?search_keywords=Java.md)[LLM agents](https://jobicy.com/jobs?search_keywords=LLM%20agents.md)[LangGraph](https://jobicy.com/jobs?search_keywords=LangGraph.md)[Amazon Bedrock](https://jobicy.com/jobs?search_keywords=Amazon%20Bedrock.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[RAG](https://jobicy.com/jobs?search_keywords=RAG.md)[Multi-agent orchestration](https://jobicy.com/jobs?search_keywords=Multi-agent%20orchestration.md)[API integration](https://jobicy.com/jobs?search_keywords=API%20integration.md)[AI evaluation](https://jobicy.com/jobs?search_keywords=AI%20evaluation.md)[Observability](https://jobicy.com/jobs?search_keywords=Observability.md)[Security engineering](https://jobicy.com/jobs?search_keywords=Security%20engineering.md)[Workflow automation](https://jobicy.com/jobs?search_keywords=Workflow%20automation.md) Sample interview questionsDescribe an LLM-powered agent you shipped to production. How did you design it, and what did you change after failures emerged?A strong answer should explain the workflow, model and tool choices, state management, permissions, evaluation metrics, and production monitoring. It should include a concrete failure mode—such as unreliable tool calls, hallucinated outputs, or latency—and describe the mitigation and resulting impact. How would you design a LangGraph-based agent that can safely execute actions in internal finance or operations systems? I would model the workflow as explicit states with scoped tool permissions, structured inputs and outputs, validation gates, audit logs, and human approval for high-risk actions. I would also implement least-privilege credentials, idempotent operations, rollback or escalation paths, and continuous evaluation of failures. What metrics would you use to evaluate whether an internal AI agent is successful? I would combine technical and business measures: task completion accuracy, tool-call success rate, groundedness, escalation rate, latency, cost per successful task, user adoption, time saved, and error severity. Metrics should be segmented by workflow and monitored over time to identify regressions. How do you turn a loosely defined request from a non-technical team into an automation project? I start by observing the current workflow and defining the desired outcome, inputs, decisions, exceptions, risks, and success criteria. I then identify what should remain human-controlled, prototype the narrowest valuable path, validate it with users, and iterate toward a dependable production workflow. How would you control cost and reliability as usage of an agent platform grows? I would instrument token, model, tool, and infrastructure costs by agent and task; select models based on task complexity; cache or reuse deterministic results; and set timeouts, retries, rate limits, and fallback paths. Reliability would be supported by tracing, automated evaluations, versioned prompts and tools, and alerting for quality or cost regressions. Opportunity details ## About this role. About Us: Wrapbook is the AI platform for production finance. We’re building a system of action that puts finance teams in control of their whole production, from payroll, to spend, to accounting. Built for feature films, TV, and commercials, Wrapbook is trusted by teams at Netflix, Paramount, Anonymous Content, and more. With backing from Andreessen Horowitz, Bessemer Venture Partners, and Jeffrey Katzenberg’s WndrCo, our team of 350+ is using AI to transform how finance teams work and empower them to do more with less. The Opportunity: Senior Software Engineer II, Applied AI (Remote – USA / Canada) We are looking for a Senior Software Engineer II, Applied AI to join our Agentic Systems team, where you’ll build AI agents that automate workflows for teams across Wrapbook. You’ll partner directly with internal teams like Marketing, Sales, Support, Operations and Finance to find high-leverage processes, then design, ship and iterate on agents that take real work off their plates. This is a chance to define how a 400+ person company runs on AI. You’ll see the impact of your work every day, while shaping the patterns, tools and standards for how we build agents at Wrapbook. What You’ll Do: * Design and build production-grade AI agents with LangGraph that automate multi-step workflows for internal teams across Wrapbook * Deploy, run and scale agents on Amazon Bedrock AgentCore, using its runtime, memory, identity and gateway capabilities to make them secure and reliable, while tracking what they cost to run and keeping it efficient as usage grows * Partner with internal teams to find high-impact workflows, draw out requirements from people who can’t hand you a spec, and turn them into agent-driven solutions, explaining clearly what each agent can and can’t reliably do * Integrate agents with Wrapbook’s internal systems, APIs and third-party tools so they can take real actions, not just answer questions * Build evaluation, observability and guardrail frameworks to measure agent quality, catch failures and keep humans in the loop where it matters * Establish reusable patterns, shared tools and best practices that let the Agentic Systems team ship new agents quickly and consistently * Own agents end to end, from prototype to production, measuring their impact on the teams they serve and iterating based on usage data and feedback * Drive adoption through clear documentation, training and enablement, so teams understand what each agent does, trust it and know how to get the most from it What You’ll Have: * 6+ years of back-end development experience with Python, TypeScript/Node.js or Java, with a track record of delivering systems built for security, scalability, availability and performance * Hands-on experience building and shipping LLM-powered agents or workflows (with models such as Claude, GPT, Llama or Mistral), including prompting, tool use and structured outputs. You can walk us through one you built: how it was designed, what broke and how you fixed it * Production experience with at least one agent or LLM framework, such as LangGraph, LangChain, LlamaIndex or AutoGen, and a solid understanding of AI architectures like RAG, reranking and multi-agent orchestration. Experience with LangGraph specifically is a plus * A security-first mindset: you think about data access, permissions and failure modes in everything you build, especially when agents can take real actions * Strong product sense and communication skills, with the ability to work directly with non-technical teams to understand their workflows and turn them into reliable automation * Comfort with ambiguity and an ownership mentality: you can take a loosely defined problem from idea to production on your own * Nice to have: experience running AWS workloads in production and knowing how to design for, deploy on and get the most out of Amazon’s services, ideally including Amazon Bedrock AgentCore This is a remote position open to candidates located in the United States or Canada. We are unable to sponsor or take over sponsorship of employment visas or work permits for this position. Applicants must be currently authorized to work in the country from which they will perform the work. Why Join Us: At Wrapbook, creativity meets technology — and not just in the product. In addition to a competitive salary and all the benefits you can expect from a fast-growing technology company, you’ll get access to a team of creative problem solvers and the chance to see your contributions make large impacts Benefits include: * Unlimited Paid Time Off * Work from anywhere in Canada and USA * Health and Dental benefits * Up to $1,500 USD/ $2,025 CAD towards IT set up for your home * Up to 2% matching RRSP / 401K * Learning and Development opportunities * Up to $50 USD/ $67.50 CAD towards Internet/Cell phone service Our Pledge to Fostering an Inclusive and Safe Workplace: Wrapbook pledges to be a harassment- and discrimination-free space for everyone, regardless of age, disability, ethnicity, gender identity or expression, nationality, neurotype, personal appearance, political affiliation, professional background, race, religion, or sexual identity or orientation. Apply Now Have we got your attention? 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