AI Engineer - Google AI & Generative Intelligence

Role: AI Engineer Google AI & Generative Intelligence

Location: Paramus, NJ (All 5 days a week onsite required)

Job Type: Full Time

Experience

Required:

10-15 years in Software Engineering | 3+ years in Artificial Generative Intelligence

We are seeking a highly experienced Senior AI Engineer with deep expertise in Google AI technologies and Generative AI. The candidate brings 10-15 years of broad software engineering experience, with the last 2+ years focused exclusively on Artificial Generative Intelligence, including designing, building, deploying, and monitoring production‑grade AI systems.

• AI Engineering
  • Design, develop, and deploy agents leveraging commercial LLMs such as Gemini (Google), GPT (OpenAI), and Claude Sonnet (Anthropic) for high‑performance, large‑context, and multimodal tasks.
  • Lead the design and implementation of AI‑powered solutions deeply integrated with Google Workspace (Docs, Sheets, Drive, Gmail, Meet), Big Query, and Lakehouse.
  • Architect and build intelligent agents and workflows using Google Agent Development Kit.
  • Leverage Google AI Studio as the primary IDE, and VSCode for AI application development and prototyping.
• Google Cloud Platform Services
  • Vertex AI for ML model training, tuning, and deployment.
  • Vertex AI Vector DBs for semantic search and retrieval.
• Design & Planning
  • Requirements gathering using Confluence for documentation and team collaboration.
  • Create detailed system architecture diagrams and AI workflows using Lucidchart.
  • Manage project delivery and sprint planning using Jira.
• Development Frameworks & Tools
  • Orchestrate LLM/SLM applications using Lang Chain, Llama Index, and Lang Graph.
  • Build multi‑agent systems with Semantic Kernel and Lang Graph.
  • Manage and optimize prompts using Lang Smith and Prompt Layer.
  • Manage code and data versioning with Git.
• Vector Databases & Semantic Search
  • Implement semantic search and Retrieval‑Augmented Generation (RAG) pipelines using Vertex AI Vector DBs and ChromaDB.
  • Design and optimize end‑to‑end RAG architectures for enterprise‑grade knowledge retrieval.
• Backend Development
  • Develop robust RESTful APIs using FastAPI (Python) or Express.js (Node.js).
  • Manage and secure APIs using Mule Soft and Apigee.
• Frontend Development
  • Drupal Content Management System (PHP Backend + JS Frontend) - Drupal 10.4, PHP 8.1.
  • Build modern user interfaces using React or Angular with Material‑UI components.
  • OAuth2 authentication.
• Development Tools & Code Quality
  • Write and debug code in VS Code with Python and Git Hub Copilot extensions.
  • Manage source code with Git Hub or Git Lab.
  • Enforce code quality and standards using Sonar Qube, ESLint, and Pylint.
• Testing & Quality Assurance
  • Conduct LLM‑specific testing using RAGAS and Deep Eval for LLM/RAG pipeline evaluation.
  • Use Lang Smith Evaluators for prompt testing and hallucination detection.
  • Write and execute unit tests using pytest.
  • Ensure output quality and reliability using Lang Chain Evaluators and custom metrics.
• Deployment & Infrastructure
  • Support on‑premise, cloud (GCP/Vertex AI), and hybrid infrastructure deployments including edge devices for local inference.

• 10-15 years of overall software engineering experience.
• 3+ years of hands‑on experience in Artificial Generative Intelligence, including LLMs, SLMs, RAG, and multi‑agent systems.
• Deep expertise in the Google AI ecosystem:
  Gemini, Vertex AI, Google ADK, Google AI Studio, and Google Workspace integrations.
• Proficiency in Python (primary) and familiarity with Node.js.
• Strong background in cloud‑native development on GCP.
• Experience with multi‑agent AI architectures using Semantic Kernel, or Lang Graph.