GenAI Full Stack Developer

GenAI Full Stack Developer/ BQML (Contract to Hire) – Remote Hybrid – Western States Residents only

Rate: $90 - $100/ Hour – Depending on Experience

MUST have 'Machine Learning Big Query' experience!

MUST reside in Western United States - no relocation!

Note: MUST be US Citizen or Green Card Holder

***NO RECRUITING AGENCIES***

***NO Corp-to-Corp***

***NO Sponsorship available***

Description

The Full Stack Engineer is a hands-on consultant responsible for designing and delivering scalable enterprise web applications.

This role requires advanced experience with React, Next.js, TypeScript, API integration, and modular application architecture. The engineer will also support Intelligent Document Processing solutions and should understand how Python, AI, and Large Language Models can be used in document workflows.

What You'll Do

• Design, build, test, and deploy enterprise applications using React, Next.js, and TypeScript.
• Create modular, reusable, and maintainable application architectures.
• Build shared components, hooks, services, utilities, and design-system patterns.
• Design scalable approaches for routing, state management, data fetching, forms, validation, and error handling.
• Integrate applications with APIs, authentication systems, enterprise data sources, and document-processing services.
• Build document upload, review, correction, approval, and exception-management experiences.
• Use Python to support document ingestion, extraction, validation, transformation, and integration.
• Apply AI and LLM capabilities to document classification, extraction, summarization, and validation where appropriate.
• Improve existing codebases by reducing duplication, tight coupling, inconsistent patterns, and technical debt.
• Implement automated testing, CI/CD, logging, monitoring, security, and performance practices.
• Own technical workstreams and provide design reviews, code reviews, and mentoring.
• Participate in client discovery, requirements analysis, demonstrations, deployment, and knowledge transfer.

Requirements

• Google Vertex AI, Bigquery, ML
• Hands-on experience deploying and operating applications on cloud infrastructure (Google, Functions, or containers).
• Experience with SQL and/or NoSQL databases
• Advanced experience with React, Next.js, TypeScript, and modern JavaScript.
• Strong understanding of React composition, hooks, rendering, and component design.
• Experience with Next.js App Router, server and client components, route handlers, middleware, and server-side rendering.
• Demonstrated ability to design modular enterprise applications with clear separation of concerns.
• Experience building reusable component libraries and working with design systems.
• Experience integrating REST APIs, backend services, and third-party platforms.
• Experience with state-management and data-fetching tools such as Redux Toolkit, Zustand, TanStack Query, or similar technologies.
• Experience building complex forms, validation workflows, and data-review interfaces.
• Experience with authentication and authorization using OAuth, OpenID Connect, JWTs, sessions, or role-based access.
• Working experience with Python for APIs, automation, data processing, or document workflows.
• Experience with Git, automated testing, CI/CD, and production deployment.
• Ability to evaluate tradeoffs involving maintainability, performance, scalability, security, and delivery speed.

Intelligent Document Processing and AI

Candidates should have practical experience with or an understanding of:

• OCR, document classification, field and table extraction
• Structured and unstructured document processing
• Confidence scoring, validation rules, and human review
• Document status tracking, exception handling, and audit history
• Python-based document ingestion, preprocessing, parsing, and transformation
• Calling document intelligence, OCR, and AI services from Python
• Large Language Models and their use in document extraction, classification, summarization, and validation
• Prompt design, structured model outputs, and hallucination risks
• The differences between OCR, trained document models, and LLM-based extraction
• Data privacy, accuracy, latency, cost, and human-in-the-loop considerations

Deep AI or data-science experience is not required.

Preferred Qualifications

• Experience leading enterprise React or Next.js projects.
• Experience modernizing or refactoring large frontend codebases.
• Experience with document-management, case-management, or workflow applications.
• Experience with Azure AI Document Intelligence, Amazon Textract, or comparable services.
• Experience with Azure OpenAI, Amazon Bedrock, or other hosted LLM services.
• Experience with FastAPI, Flask, Node.js, or backend API development.
• Experience with AWS or Azure application hosting and integration services.
• Cloud experience is helpful but is not the primary focus of the role.

Professional Skills

• Strong application-design and problem-solving skills.
• Ability to translate business requirements into practical software designs.
• Strong consulting, communication, documentation, and code-review skills.
• Ability to independently own technical workstreams.
• Ability to identify architectural risks, technical debt, and delivery blockers.
• Ability to mentor developers and establish consistent engineering practices.

Critical Success Factors

• Ability to independently deliver production-ready React and Next.js applications.
• Strong understanding of modular enterprise application architecture.
• Ability to create reusable patterns without unnecessary complexity.
• Ability to integrate Intelligent Document Processing into enterprise applications.
• Practical understanding of Python, AI, and LLM-supported document workflows.
• Commitment to code quality, testing, accessibility, security, performance, and maintainability.