Full Stack AI Engineer

Company Overview

Vinova is an award-winning development company specializing in mobile, web, and enterprise applications. Since 2010, we serve global clients across IoT, blockchain, fintech, networking, and ecommerce, delivering quality, flexible, and fast solutions through passionate collaboration.

Job Summary

Design and build scalable, reliable software systems with modern technologies, focusing on full-stack and AI-powered applications. Collaborate with government teams and product management to deliver accessible, high-quality features and provide customer support.

Responsibilities

Design and develop scalable, reliable, and maintainable software systems using modern technologies such as React.js, TypeScript, and Node.js

Build full-stack features across frontend, backend, APIs, data, and AI systems to meet product requirements

Develop production-grade applied AI-powered applications and developer tools, including LLM workflows using RAG, tool calling, structured outputs, agents, and human-in-the-loop patterns

Build evaluation pipelines using golden datasets, regression tests, deterministic evaluators, and LLM-as-a-judge to ensure AI system quality

Implement observability, monitoring, guardrails, fallbacks, and validation mechanisms to maintain reliable AI systems balancing model quality, latency, reliability, maintainability, and cost

Maintain automated tests (unit, integration, E2E), CI/CD pipelines, and technical documentation including API specifications, troubleshooting guides, and system architecture diagrams

Analyze complex system behaviors and logs to troubleshoot and debug software issues effectively

Translate customer feedback and production issues into reusable product improvements

Collaborate with Product Management to provide L1/L2 customer support and resolve technical issues

Work directly with government teams on discovery, demos, Proof-of-Concepts, architecture discussions, onboarding, integrations, and troubleshooting

Gain knowledge and assist in debugging and remediating WCAG accessibility issues on production websites

Communicate technical trade-offs and quality standards clearly to diverse stakeholders

Preferred competencies and qualifications

Knowledge of Docker, Infrastructure as Code, and Bash scripting

Passion for building inclusive technology and applying or developing expertise in WCAG 2.2 standards and assistive technologies

Willingness to learn digital accessibility regulations and Web Content Accessibility Guidelines (WCAG) 2.2 Level A and AA requirements

Experience writing code that meets accessibility standards such as WCAG

Familiarity with screen readers such as VoiceOver, NVDA, and TalkBack