AI Fullstack Engineer

Mroads is looking for an "AI Fullstack Engineer" for one of the direct clients. This is a remote opportunity with travel once a quarter to Bethesda, MD.Job Responsibilities

• Develop and maintain scalable full-stack applications using JavaScript technologies with expertise in React, Node.js, GraphQL, and NX.
• Design, develop, and integrate AI-powered features leveraging Large Language Models (LLMs), Langchain, Generative AI, and intelligent automation capabilities.
• Build and consume APIs for AI/LLM services, including prompt orchestration, model integration, and retrieval-based solutions.
• Collaborate with product, engineering, and AI teams to identify and implement AI-driven user experiences and business workflows.
• Implement DevOps best practices and contribute to continuous improvement of the software development lifecycle.
• Utilize Git for version control and collaborative development across distributed teams.
• Implement and manage CI/CD pipelines to ensure reliable, secure, and efficient code delivery.
• Deploy, monitor, and optimize cloud-native applications and AI services in Kubernetes environments.
• Architect innovative, scalable, and secure solutions while contributing to platform engineering initiatives.
• Evaluate emerging AI technologies, frameworks, and tools to drive innovation and improve development efficiency.
• Ensure application quality through automated testing, code reviews, observability, and performance optimization.
• Demonstrate a passion for delivering high-quality, customer-focused solutions.

Requirements

• Proven experience as a Full Stack JavaScript Developer with expertise in React, Node.js, GraphQL, and NX.
• Hands-on experience integrating AI/ML services, Large Language Models (LLMs), and Generative AI capabilities into enterprise applications.
• Experience working with AI platforms and frameworks such as OpenAI APIs, Anthropic, Gemini, LangChain, LlamaIndex, Vector Databases, RAG (Retrieval-Augmented Generation), or similar technologies.
• Strong understanding of prompt engineering, AI application design patterns, and responsible AI practices.
• Experience building and consuming RESTful APIs, GraphQL APIs, and AI service integrations.
• Proficiency in Kubernetes and containerized application deployment.
• Experience with CI/CD pipelines, DevOps practices, and cloud platforms such as AWS, Azure, or Google Cloud.
• Strong architectural skills with the ability to design scalable, resilient, and secure solutions.
• Knowledge of observability, monitoring, logging, and performance tuning in distributed systems.
• Excellent problem-solving, communication, and collaboration skills.
• Passionate about software quality, innovation, and leveraging AI technologies to solve business challenges.