Senior Fullstack AI Engineer(Vertex AI/ .NET/React) :: Remote :: W2 Position

Role:Senior Full Stack AI Engineer (Vertex AI / .NET / React)
Location: 100% Remote
Position Overview
We are looking for a highly skilled Senior Full Stack AI Engineer with strong experience in Generative AI, LLM fine-tuning, Google Vertex AI, .NET development, and React. The ideal candidate will build, deploy, and maintain production-ready AI applications, including AI-powered chat assistants, retrieval-augmented generation (RAG) solutions, and vector search capabilities.
The candidate should be comfortable managing the entire development lifecycle, from solution design and data preparation to deployment, monitoring, and production support.
Key Responsibilities

• Design, implement, and deploy fine-tuned LLMs using Google Vertex AI and Gemini models.
• Develop supervised fine-tuning (SFT) workflows using LoRA adapters.
• Create, validate, and maintain JSONL training datasets from structured and unstructured data sources.
• Build data pipelines using business rules, SQL schemas, standard operating procedures (SOPs), and expert-curated datasets.
• Evaluate model performance, analyze training metrics, and troubleshoot overfitting, underfitting, data imbalance, and model drift.
• Develop RAG architectures, vector embeddings, semantic search, and retrieval solutions.
• Build and maintain backend services and REST APIs using C#, .NET, and ASP.NET Core.
• Develop responsive, user-friendly frontend applications using React and modern JavaScript.
• Integrate Oracle, SQL Server, and MongoDB Atlas with AI applications and data pipelines.
• Implement vector search capabilities using MongoDB Atlas.
• Manage cloud deployments and AI model endpoints using Google Cloud Platform (Google Cloud Platform).
• Automate build, testing, and deployment workflows using Docker, CI/CD pipelines, and GitHub Actions.
• Implement real-time AI response streaming and session-aware conversational workflows.
• Monitor AI model performance, manage model versions, and implement rollback and retraining strategies.
• Troubleshoot application, cloud infrastructure, networking, and database connectivity issues.
• Collaborate with stakeholders and independently deliver solutions from design and development through testing, deployment, and production support.

Required Technical Skills

• Proven experience building and deploying fine-tuned LLMs in production environments.
• Hands-on experience with Google Vertex AI and Gemini models.
• Strong experience with supervised fine-tuning (SFT) and LoRA adapters.
• Expertise in creating and validating JSONL training datasets.
• Experience developing multi-source training data pipelines.
• Strong understanding of model evaluation, tuning, and performance monitoring.
• Experience with RAG, vector embeddings, and semantic search.
• Strong C#, .NET, and ASP.NET Core REST API development skills.
• Experience building applications using React and JavaScript.
• Strong SQL skills and experience integrating Oracle and SQL Server databases.
• Experience with MongoDB Atlas and Vector Search.
• Hands-on experience with Google Cloud Platform services, including Vertex AI and Cloud Storage.
• Experience with Docker, CI/CD, GitHub Actions, and containerized deployments.
• Strong troubleshooting skills across cloud, networking, application, and database environments.
• Ability to independently manage projects from solution design through production deployment.

Preferred Qualifications

• Experience with Gemini 2.5 Flash.
• Familiarity with Google's text-embedding-005 model.
• Experience developing lightweight classifier models for AI routing and orchestration.
• Knowledge of continuous fine-tuning and two-pass training methodologies.
• Experience implementing training data provenance, traceability, and audit trails.
• Experience with Server-Sent Events (SSE) for streaming AI responses.
• Familiarity with Vite, PrimeReact, or similar frontend frameworks.
• Experience with model versioning, endpoint lifecycle management, and rollback strategies.
• Previous experience developing AI-powered chatbots or conversational applications.
• Experience optimizing AI application latency, token usage, and inference costs.

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Ideal Candidate Profile
The ideal candidate combines hands-on production LLM fine-tuning expertise with strong full-stack development skills. They should be able to build reliable AI solutions using Vertex AI and Gemini while developing scalable backend services in .NET and interactive frontend applications in React.