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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - Platform Intelligence - **Company:** The Nukleus LLC - **Location:** Issaquah, WA, United States - **Salary:** $124,800.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software as a Service, Encodings, Fault Tolerance, JSON, PostgreSQL, Node.Js, Software Engineering, TypeScript, Unstructured Data, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, Front End Software Development, Data Pipelines - **Published:** June 24, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=3b14992237d2ecf2 ## About the Role Do you have experience in Software engineering?, * Proven experience shipping AI-powered features in production - RAG pipelines, LLM integrations, or agent systems used by real people at scale, not demos or prototypes * Deep hands-on experience with LLM APIs (Anthropic, OpenAI), embedding-based search, and RAG architecture - including chunking strategy, retrieval evaluation, and prompt engineering for structured outputs * Strong full-stack engineering fundamentals - you are comfortable in React on the frontend and can own backend logic in TypeScript/Node, Supabase Edge Functions, and Postgres * Experience building data pipelines over mixed structured and unstructured data - PDF extraction, JSON normalization, and vector storage - and a disciplined approach to evaluating model outputs over time * A genuine product instinct - you know when AI adds real value versus when it is noise, and you are willing to make that call even when it means building less * Ability to communicate technical decisions clearly to non-technical stakeholders - founders, athlete partners, and sports industry advisors who care about outcomes, not architecture diagrams * Self-directed and entrepreneurial - you surface the next problem before being asked, and you have opinions about what Nukleus should build that you are willing to defend Bonus Points * Experience at a company where AI was central to the product, not a bolt-on - ideally a fintech, sports tech, media, or creator economy platform * Hands-on work with multi-agent architectures or autonomous tool-calling workflows - orchestration, memory, handoff patterns, and the failure modes that come with them * Understanding of the sports industry - how contracts are structured, how NIL deals work, how athlete brands are valued * Familiarity with pgvector or dedicated vector databases (Pinecone, Weaviate) and the trade-offs between them at different dataset scales * Experience designing AI features for mobile-first or data-rich SaaS products, with an eye toward latency, streaming responses, and graceful degradation ## Description We are looking for an AI engineer who thinks in possibilities, not limitations. We have mapped out our AI based initiatives and we need the right engineer to walk in, evaluate what we have planned, and own the implementation. That means you may validate the architecture and execute it, or you may identify a better path and make the case for it. Either outcome is the right one. What we are not looking for is someone who simply executes instructions. We want an engineer with enough conviction and experience to push back when it matters and build with confidence when the direction is right. Your mandate also extends to the entire platform. You will look at every feature we have built - contract management, financial tracking, NIL deal flow, social metrics, the Collab Hub, agent and advisor workflows - and ask what becomes possible when intelligence runs through all of it. You will use the proprietary data we store to create experiences that feel less like software and more like having the smartest analyst in professional sports sitting next to you at all times. You should have strong technical fundamentals, genuine excitement about what AI can do right now, and the creativity to imagine applications that nobody has thought of yet. ## Related Videos - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [AI in Production: applied AI & enterprise use cases](https://www.wearedevelopers.com/videos/100130-ai-in-production-applied-ai-enterprise-use-cases) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Postgres in the Age of AI (and Devin)](https://www.wearedevelopers.com/videos/1042-postgres-in-the-age-of-ai-and-devin) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)