Senior AI Engineer (Full Stack)

OUR VISION The digital world was built around platforms, not people. AI is rewriting what software can do, and we have a narrow window to make sure that future puts the individual at the center rather than further behind. A future where your digital identity belongs to you, travels with you, and gives you real agency in how you show up online. Where you set the rules, hold the keys, and actually benefit from your own data. We are building toward that future across every layer it requires: the infrastructure that makes it possible, the standards that make it interoperable, and the experiences that bring it to life for the people who use it.WHAT YOU WILL DO As a Senior AI Engineer (Full Stack) at Blockchains, you will be the bridge between our AI systems and the users who rely on them. You will deliver AI-powered products and features end-to-end, not just integrating an API, but defining the AI experience, engineering what powers it, and carrying it through to a polished, production-grade interface. You will ship fast, caring as much about how AI features feel as how they work. You will operate with an MVP-first, rapid-iteration mindset, moving from idea to working prototype quickly, then taking the strongest ideas all the way to polished, production-grade experiences. Responsibilities include, but are not limited to: Product and Design Collaboration:Partnering with product managers, designers and external vendors to define how AI interactions should feel: response tone, citation style, error states, loading experiences, and streaming behavior. Translating real-world usage patterns directly into prompt improvements, UX adjustments, and feature iterations, closing the loop between what users experience and what ships next. Building AI POCs rapidly to test hypotheses with stakeholders before committing to full builds. Front-End AI Interfaces:Building real-time AI interfaces in React, Next.js, and TypeScript: streaming responses, citation display, agent status indicators, and interactive document experiences. Owning the full feature lifecycle from back-end API to browser, ensuring AI features are fast, accessible, and reliable under production load. LLM Integration and Context Pipelines:Integrating LLM APIs with streaming, prompt engineering, and error handling across the full stack. Consuming and extending context augmentation pipelines: vector RAG, CAG, Text-to-SQL, MCP-based context engineering, built by the AI systems team. Privacy and Delivery:Applying data privacy best practices at every layer: PII handling, GDPR/CCPA compliance, and encryption from the UI to the API. Deploying AI features on AWS using Docker/Kubernetes, and GitLab CI/CD. WHAT YOU WILL NEED TO SUCCEED You have strong product instincts, and you move fast. You can go from idea to working prototype in a day, and you know how to take that prototype to a polished product experience. You think about the user first, and you bring that lens to every technical decision. You exercise strong judgment on when to build versus buy and how to scope an MVP versus a production system, and you have a proven track record of building AI POCs and prototypes that ship to real users. You treat AI safety as a first-class concern, applying prompt injection awareness, output validation, access controls, and data leakage prevention at every layer, from the API call to the browser. You use Claude Code or OpenAI Codex as a core part of your development workflow, and you have a track record of mentoring junior engineers and helping them ship better AI product work.YOUR EDUCATION AND EXPERIENCE You have at least 2 years of experience delivering AI-powered product features, built on a minimum of 5 years of full-stack software engineering experience. Strong Python skills are required, and familiarity with Node.js or .NET is a plus. A bachelor’s degree in Computer Science, Engineering, or a related field is preferred but not required; a portfolio of shipped AI product work speaks louder than credentials. You have working knowledge of LLM APIs, including prompt & context engineering, streaming integration, and handling edge cases in production, and you are familiar with context augmentation strategies, vector RAG, CAG, Text-to-SQL, and MCP-based context engineering, sufficient to integrate and extend existing pipelines. You bring strong front-end skills in React, Next.js, and TypeScript, with direct experience building streaming, real-time, or AI-driven user interfaces. You have a practical understanding of data privacy (PII handling, GDPR/CCPA) and encryption applied across front-end and back-end layers, along with familiarity with AWS, Docker, Kubernetes, and GitLab. Experience working directly with designers and product managers to define AI interaction patterns, exposure to agent orchestration frameworks such as LangChain, LlamaIndex, or LangGraph, and exposure to local open-source models and fine-tuning concepts are valuable assets. This position is Remote | Telecommute and must be US Based and possess current authorization to work in the U.S. without sponsorship. Apply To This Job