Full Stack Engineer

Title: Full Stack AI Developer

Location: Austin, TX(Onsite Local)

Duration: W2Job Description: Must be available for an interview today or Monday.

Candidate Requirements: Senior-level engineering capability (Level 7–8).Ability to work independently and own end-to-end development. Strong communication and stakeholder collaboration skills. Austin, TX local candidates preferred.10+ years of experience

Job Summary: We are seeking an experienced Full Stack AI Developer to design, develop, and deploy intelligent, AI-powered applications. The ideal candidate will have strong full-stack engineering expertise combined with hands-on experience integrating Generative AI, Large Language Models (LLMs), and AI-driven capabilities into enterprise applications. This role requires an individual who can independently drive application development, build scalable backend services, develop modern user interfaces, and integrate AI/ML solutions into production-ready systems.

Key Responsibilities: Design, develop, and maintain scalable full-stack applications. Build modern frontend applications using React, Angular, or similar frameworks. Develop backend services and RESTful APIs using Python, Java, Node.js, or equivalent technologies. Integrate Generative AI capabilities and LLM-based solutions into enterprise applications. Work with frameworks such as LangChain, LangGraph, or similar AI orchestration tools. Develop AI-powered workflows, intelligent agents, and RAG-based applications. Integrate enterprise data sources, vector databases, and external APIs. Optimize application performance, scalability, security, and reliability. Collaborate with architects, product owners, and cross-functional engineering teams. Support application deployment using Docker, Kubernetes, and CI/CD pipelines. Required Technical SkillsStrong full-stack development experience. Frontend: React, Angular, JavaScript, TypeScript, HTML5, CSS.Backend: Python, FastAPI, Java, Node.js, or Spring Boot.

AI/ML: Generative AI, LLMs, Prompt Engineering, RAG.AI Frameworks: LangChain, LangGraph, LlamaIndex, or equivalent. API Development: REST APIs, microservices, API integration. Databases: PostgreSQL, SQL Server, MongoDB, or equivalent. Vector Databases: Pinecone, FAISS, Chroma, or similar. Cloud: Azure, AWS, or GCP.DevOps: Docker, Kubernetes, Git, CI/CD.

Preferred Qualifications: Experience developing production-grade AI applications. Experience building agentic AI workflows and multi-agent systems. Knowledge of Azure OpenAI, OpenAI APIs, or equivalent LLM platforms. Experience with enterprise application architecture and distributed systems. Strong debugging, problem-solving, and technical leadership capabilities.