Google AI Developer

Job Title: Google AI Full Stack Developer Location: Hartford, CT Employment type : 6 months Contract To Hire We are seeking a highly skilled Google AI Full Stack Developer to design, build, and deploy AI-driven applications using the Google Cloud AI ecosystem, including Vertex AI, Gemini models, and Generative AI Studio. The ideal candidate will have end-to-end expertise across frontend development, backend integration, and AI/ML pipeline implementation within the Google Cloud Platform (GCP) environment. This role blends software engineering, AI integration, and cloud architecture — ideal for developers passionate about building intelligent, scalable, and secure AI solutions. Key Responsibilities AI & Generative AI Development • Design and implement AI-powered full-stack applications using Google Vertex AI, Generative AI Studio, and Gemini APIs. • Integrate LLM (Large Language Model) and multimodal AI capabilities into business workflows and user-facing apps. • Build Retrieval-Augmented Generation (RAG) and chatbot applications with Google Vertex AI Search and Embeddings API. Frontend Development • Build responsive, user-centric interfaces using ReactJS, Angular, or Vue.js, integrated with AI backend APIs. • Develop interactive dashboards, chatbot UIs, and visualization tools for AI insights. • Ensure performance optimization, accessibility, and secure frontend data handling. Backend Development • Design and implement secure APIs and microservices using Python (FastAPI/Flask), Node.js, or Go. • Integrate with Google Cloud Functions, Cloud Run, BigQuery, and Vertex AI endpoints for data and model access. • Manage user sessions, authentication, and API rate control using Google Identity and IAM policies. Cloud & MLOps Integration • Develop and deploy ML workflows using Vertex AI Pipelines and GCP AI Infrastructure. • Automate builds and deployments with Cloud Build, Terraform, or GitHub Actions. • Collaborate with Data Scientists and ML Engineers to operationalize and monitor models. • Optimize AI workloads for cost, scalability, and latency in production. Security & Governance • Implement RBAC, API Gateway, and secure data handling practices. • Ensure compliance with enterprise and cloud security standards (IAM, VPC, data encryption). • Maintain code quality through testing, reviews, and vulnerability scanning. Required Skills & Qualifications • 5+ years of experience in full-stack application development. • 2+ years of hands-on experience with Google Cloud AI — especially Vertex AI, Gemini API, or Generative AI Studio. • Strong proficiency in ReactJS, Node.js, and Python (or equivalent backend language). • Solid understanding of RESTful APIs, microservices architecture, and event-driven systems. • Experience deploying applications with Docker and Kubernetes. • Familiarity with MLOps concepts, AI model lifecycle management, and data engineering practices. • Experience with BigQuery, Cloud Storage, and Pub/Sub for data flow and analytics. Preferred Qualifications • Certifications in Google Cloud Professional Developer, AI Engineer, or Data Engineer. • Experience implementing Generative AI, chatbots, or RAG pipelines in production. • Knowledge of LangChain, Vector Databases (like Pinecone or FAISS), and custom embedding models. • Familiarity with CI/CD, DevSecOps, and cloud observability tools (Stackdriver, Prometheus). • Exposure to other cloud AI platforms such as AWS Bedrock, Azure OpenAI, or IBM WatsonX.