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Full Stack AI Engineer (Gen AI) | W2 Only | 100% Remote

Trebecon LLCUnited States🇺🇸United StatesPosted 17 Jul 2026

Quick Overview

Work Type
Remote
Level
Mid Senior

Job Description

Role: Full Stack AI Engineer (Generative AI)

Location: Remote

Key Responsibilities
  • Design, develop, and maintain scalable full-stack web applications.
  • Build AI-powered applications leveraging Large Language Models (LLMs) such as OpenAI GPT, Anthropic Claude, Google Gemini, and open-source models.
  • Develop intelligent AI Agents capable of planning, reasoning, and executing multi-step tasks.
  • Design and implement Retrieval-Augmented Generation (RAG) architectures using enterprise data sources.
  • Integrate AI capabilities into existing Java, .NET, or Node.js enterprise applications.
  • Develop RESTful APIs and microservices using Python (FastAPI/Flask) or Node.js.
  • Build responsive frontend applications using React.js, Next.js, or Angular.
  • Implement vector search solutions using Pinecone, Weaviate, ChromaDB, Milvus, or FAISS.
  • Optimize prompts, embeddings, context retrieval, and AI workflows for accuracy and performance.
  • Integrate enterprise systems including Microsoft Graph, Salesforce, ServiceNow, Jira, SharePoint, and other SaaS platforms.
  • Develop secure, scalable cloud-native applications on AWS, Azure, or Google Cloud Platform.
  • Containerize applications using Docker and deploy through Kubernetes and CI/CD pipelines.
  • Monitor AI application performance, latency, token usage, and model quality.
  • Follow AI governance, responsible AI, and security best practices.
 

Required Skills

Frontend
  • React.js / Next.js, TypeScript / JavaScript, HTML5, CSS3, Tailwind CSS / Material UI
Backend
  • Python (FastAPI, Flask, Django), Java (Spring Boot), .NET Core ( Core), Node.js (Express/NestJS), REST APIs, GraphQL (preferred)
Generative AI
  • OpenAI API, Anthropic Claude API, Google Gemini, Azure OpenAI, Prompt Engineering, Function Calling, Structured Outputs, AI Agent Development, Multi-Agent Systems, Model Context Protocol (MCP)
AI Frameworks
  • LangChain, LangGraph, LlamaIndex, CrewAI or AutoGen (preferred), Semantic Kernel (preferred)
RAG & Search
  • Retrieval-Augmented Generation (RAG)
  • Vector Databases
    • Pinecone, Weaviate, Milvus, Chroma, FAISS
  • Embeddings, Semantic Search
Databases
  • PostgreSQL, MySQL, SQL Server, MongoDB, Redis
Cloud & DevOps
  • AWS / Azure / Google Cloud Platform, Docker, Kubernetes, GitHub Actions, Azure DevOps, CI/CD Pipelines, Terraform (preferred)
 

Preferred Qualifications
  • Experience building enterprise AI Copilots and AI Assistants.
  • Experience developing Agentic AI solutions.
  • Hands-on experience with Microsoft Copilot Studio or Azure AI Foundry.
  • Experience integrating Databricks, Snowflake, or Microsoft Fabric with AI applications.
  • Familiarity with AI observability tools such as LangSmith, Arize AI, or PromptLayer.
  • Knowledge of AI security, responsible AI, and model governance.
  • Experience working in Agile/Scrum environments.
 







 

Skills

Django
Docker
Express
FastAPI
Flask
Material UI
Microservices
MongoDB
MySQL
NestJS
Next.js
Node.js
SQL
SQL Server
Spring
Spring Boot
AWS
Scrum
Snowflake
Agile
Angular
Azure
CSS
Databricks
.NET
GPT
Generative AI
GitHub Actions
Google Cloud
GraphQL
Java
JavaScript
Jira
Kubernetes
PostgreSQL
Python
REST
React
Redis
Tailwind CSS
Terraform
TypeScript

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