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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.
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Compensation Range: $183K - $283.5K
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 11,520 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Wrapbook, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,688 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Wrapbook AI Hiring
Wrapbook has 2 open AI roles right now. They're hiring across AI Software Engineer. Positions span Seattle, WA, US, US. Compensation range: $283K - $283K.
Location Context
AI roles in Austin pay a median of $208,000 across 317 tracked positions. That's 3% below the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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