Full Stack AI Engineer

Company OverviewVinova 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 SummaryDesign 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.ResponsibilitiesDesign and develop scalable, reliable, and maintainable software systems using modern technologies such as React.js, TypeScript, and Node.jsBuild full-stack features across frontend, backend, APIs, data, and AI systems to meet product requirementsDevelop production-grade applied AI-powered applications and developer tools, including LLM workflows using RAG, tool calling, structured outputs, agents, and human-in-the-loop patternsBuild evaluation pipelines using golden datasets, regression tests, deterministic evaluators, and LLM-as-a-judge to ensure AI system qualityImplement observability, monitoring, guardrails, fallbacks, and validation mechanisms to maintain reliable AI systems balancing model quality, latency, reliability, maintainability, and costMaintain automated tests (unit, integration, E2E), CI/CD pipelines, and technical documentation including API specifications, troubleshooting guides, and system architecture diagramsAnalyze complex system behaviors and logs to troubleshoot and debug software issues effectivelyTranslate customer feedback and production issues into reusable product improvementsCollaborate with Product Management to provide L1/L2 customer support and resolve technical issuesWork directly with government teams on discovery, demos, Proof-of-Concepts, architecture discussions, onboarding, integrations, and troubleshootingGain knowledge and assist in debugging and remediating WCAG accessibility issues on production websitesCommunicate technical trade-offs and quality standards clearly to diverse stakeholdersPreferred competencies and qualificationsKnowledge of Docker, Infrastructure as Code, and Bash scriptingPassion for building inclusive technology and applying or developing expertise in WCAG 2.2 standards and assistive technologiesWillingness to learn digital accessibility regulations and Web Content Accessibility Guidelines (WCAG) 2.2 Level A and AA requirementsExperience writing code that meets accessibility standards such as WCAGFamiliarity with screen readers such as VoiceOver, NVDA, and TalkBack