Engineer Jobs in Web3

Compensation: Competitive base salary based on experience

ABOUT PERFORMANCE AI

Mission: make Performance AI easier to run internally and easier for customers to adopt successfully.

Performance AI helps organizations deploy governed AI workflows across business operations, customer delivery and enterprise systems. We work with real customers in healthcare, enterprise operations, and regulated

environments where AI adoption must be governed, measurable, and operationally useful.

ABOUT THE ROLE

This is a high-ownership engineering role for someone who thrives at the intersection of full-stack development and AI systems. You will build the interfaces, backend services, and AI pipelines that power Performance AI's platform — from intuitive front-end experiences to the retrieval, reasoning, and integration layers that make our AI useful in the real world.

This is not a support or maintenance role. It is for someone who takes architectural ownership, ships

production-quality code, and can navigate complexity across frontend, backend, and AI layers simultaneously.

WHAT YOU'LL OWN — FRONTEND DEVELOPMENT

• Build modern, responsive user interfaces using React.js, Next.js, and TypeScript.

• Implement server-side rendering (SSR) and static site generation (SSG) using Next.js.

• Translate UI/UX designs into high-quality, reusable components with Tailwind CSS or >

• Develop intuitive interfaces for AI-powered features, including chat experiences, workflow builders, and data interaction layers.

WHAT YOU'LL OWN — BACKEND DEVELOPMENT & AI INTEGRATIONS

• Design, architect, and maintain modular, scalable, and secure backend services using Node.js, Express, and TypeScript, following clean module-based folder structures.

• Build robust RESTful and GraphQL APIs with industry-standard validation using Joi, centralized error handling, and async/await patterns.

• Lead development of integration layers connecting external systems — Google Drive, OneDrive, and third-party APIs — into unified workflows.

• Collaborate with cross-functional teams to deliver end-to-end solutions and own technical decisions across backend architecture, integrations, and AI systems.

• Design and implement RAG (Retrieval-Augmented Generation) pipelines, including data ingestion, chunking, embedding, indexing, and retrieval strategies.

• Build and orchestrate LLM-powered workflows using LangChain and LlamaIndex, including multi-step reasoning, tool usage, and agent-like behaviors.

• Integrate structured and unstructured data sources into AI systems with a focus on context relevance and

performance.

• Optimize prompt design, response quality, latency, and cost for production LLM applications.

• Optimize data access layers for MongoDB (aggregation pipelines, indexing, transactions) and MySQL (joins, indexing strategies, query optimization).

• Implement microservices and event-driven systems using queues, background workers, and efficient

communication patterns.

• Containerize backend services using Docker, maintain environment parity across dev/staging/production, and implement CI/CD workflows.

• Integrate Stripe and other payment gateways with secure webhook handling, subscription logic, billing flows, and PCI-friendly design patterns.

• Develop healthcare EMR integrations using HL7/FHIR with a strong focus on compliance, data normalization, mapping, and secure API interactions.

• Work with blockchain technologies (Ethereum via ethers.js) to implement wallet flows, contract interactions, event listeners, and secure on-chain/off-chain data orchestration.

WHAT WE'RE LOOKING FOR

• 5+ years of full-stack engineering experience with production-grade React/Next.js and Node.js/TypeScript applications

• Hands-on experience building and deploying RAG pipelines, LLM integrations, or AI-powered products

• Solid understanding of API design (REST and GraphQL), async patterns, and backend architecture

• Experience with MongoDB and/or MySQL at scale, including schema design and query optimization

• Familiarity with Docker, CI/CD pipelines, and maintaining environment parity across deployment stages

• Strong written communication and ability to work autonomously across time zones

• High ownership, urgency, and follow-through — you ship and you care about quality

STRONG PREFERENCE FOR

Experience with healthcare data standards (HL7/FHIR); blockchain/Web3 integrations (ethers.js, Solidity); payment gateway integrations (Stripe); LangChain or LlamaIndex in production; or experience in regulated industries such as healthcare, fintech, or enterprise SaaS.

FIT

You like building more than theorizing. You are comfortable owning decisions, working across the stack, and shipping in ambiguous environments. This is not a fit if you need heavy direction, prefer isolated backend or frontend work only, or are looking for a slow-paced environment.

SUCCESS IN THE FIRST 90 DAYS

By Day 30: understand the platform architecture, ship your first production feature, and integrate with at least one external system.

By Day 60: own a meaningful backend or AI pipeline component end-to-end.

By Day 90: drive architectural decisions and contribute to our AI integration roadmap.

APPLICATION QUESTIONS

1. Describe a RAG pipeline or LLM-powered feature you have built in production. What were the key design decisions?

2. What is the most complex API integration you have owned? How did you handle reliability, error handling, and edge cases?

• 3. What would you do in your first 30 days to get up to speed on a new codebase?