AI Engineer – Google AI & Generative Intelligence

Role: AI Engineer Google AI & Generative Intelligence

Location:

Paramus, NJ (All the 5 days a week onsite is required)
Job Type: Full Time Experience

Required:

10 15 Years in Software Engineering | 3+ Years in Artificial Generative Intelligence Role Overview

We are seeking a highly experienced Senior AI Engineer with deep expertise in Google AI technologies and Generative AI. The ideal 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. This role demands mastery of the Google ecosystem including Google Workspace, Google Agent Development Kit (ADK), and Vertex AI alongside a strong command of modern LLM/SLM frameworks, cloud-native infrastructure, and MLOps best practices.

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 (ADK). Leverage Google AI Studio as the primary IDE, VSCode for AI application development and prototyping. Utilize Google Cloud Platform (GCP) Services Including Vertex AI for ML model training, tuning, and deployment Vertex AI Vector DBs for semantic search and retrieval

Lead 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.

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.

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.

Develop robust RESTful APIs using FastAPI (Python) or Express.js (Node.js). Manage and secure APIs using Mulesoft, Apigee.

Drupal Content Management System (PHP Backend + JS Frontend) - Drupal 10.4, PHP 8.1 Build modern user interfaces using React or Angular. Utilize Material-UI for consistent, accessible, and modern UI components. OAuth2 authentication.

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.

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.

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 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.