AI Engineer – Google AI & Generative Intelligence – Full Time Role

Harper Adams University; Paramus (NJ); On-site; USD 150,000 - 190,000; Full time

Job summary

We are seeking a highly experienced Senior AI Engineer with deep expertise in Google AI technologies and Generative AI. The candidate will bring 10–15 years of software engineering experience, with the last 2+ years focused on AI, MLOps, and production-grade AI systems.

Responsibilities include designing, building, deploying, and monitoring AI agents that leverage Gemini, GPT, and Claude, integrating with Google Workspace, Vertex AI, and supporting data pipelines, APIs, and front-end workflows.

Qualifications

• 10–15 years of overall software engineering experience.
• 3+ years in Artificial Generative Intelligence, including LLMs and multi-agent systems.
• Deep expertise in Google AI ecosystem: Gemini, Vertex AI, Google ADK, Google Workspace integrations.
• Proficiency in Python; familiarity with Node.js.
• Strong background in cloud-native development on GCP.

Responsibilities

• Design, develop, and deploy Agents leveraging LLMs for high-performance tasks.
• Lead Google Workspace integration with Docs, Sheets, Drive, Gmail and more.
• Plan requirements and architecture using Confluence and Jira.
• Develop AI workflows using LangChain, LangGraph, and Semantic Kernel.
• Implement semantic search and RAG pipelines with Vertex AI Vector DBs and ChromaDB.
• Build robust RESTful APIs with Python/ FastAPI or Node.js/Express.

Skills

Software engineering

Generative AI

Python

Cloud computing

Tools

Vertex AI

Google ADK

LangChain

ChromaDB

Job description

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.

Key Responsibilities

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.

Google AI & Workspace Integration

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.

Design & Planning

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.

Development Frameworks & Tools

Orchestrate LLM/SLM applications using LangChain, LlamaIndex, and LangGraph. Build multi-agent systems with Semantic Kernel, and LangGraph. Manage and optimize prompts using LangSmith and PromptLayer. 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 Mulesoft, 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. Utilize Material-UI for consistent, accessible, and modern UI components. OAuth2 authentication.

Development Tools & Code Quality

Write and debug code in VS Code with Python and GitHub Copilot extensions. Manage source code with GitHub or GitLab. Enforce code quality and standards using SonarQube, ESLint, and Pylint.

Testing & Quality Assurance

Conduct LLM-specific testing using RAGAS and DeepEval for LLM/RAG pipeline evaluation. Use LangSmith Evaluators for prompt testing and hallucination detection. Write and execute unit tests using pytest. Ensure output quality and reliability using LangChain Evaluators and custom metrics.

Deployment & Infrastructure

Support on-premise, cloud (GCP/Vertex AI), and hybrid infrastructure deployments including edge devices for local inference.

Required Qualifications

• 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 LangGraph.