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

Saransh Inc; Paramus (NJ); On-site; USD 190,000 - 260,000; Full time

Job summary

Saransh Inc is seeking a senior AI engineer with deep expertise in Google AI technologies and Generative AI, based in Paramus, NJ onsite. The role requires 10-15 years in software engineering and 3+ years focused on Generative AI, including production-ready AI systems.

You will design, deploy, and monitor agents using Gemini, GPT, Claude Sonnet, and integrate with Google Workspace, Vertex AI, and BigQuery. Strong Python skills and cloud-native GCP work are essential.

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, Vertex AI, Google ADK and Workspace integrations.
• Proficiency in Python (primary) and familiarity with Node.js.
• Cloud-native development experience on GCP.
• Experience with multi-agent AI architectures using Semantic Kernel or LangGraph.

Responsibilities

• Design, develop, and deploy AI agents and workflows with Google AI tools.
• Integrate AI solutions with Google Workspace, BigQuery and Lakehouse.
• Architect intelligent agents and RAG pipelines for enterprise knowledge retrieval.
• Lead project delivery, planning, and RESTful API development.
• Employ LangChain, LangSmith, and evaluation tools for quality assurance.

Skills

Python programming

AI engineering

Cloud experience

Tools

Google Vertex AI

LangChain

LangGraph

ChromaDB

VSCode

GitHub Copilot

Git

LangSmith

Job description

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

Role Overview

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.

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.
  • Lead the design and implementation of AI‑powered solutions deeply integrated with Google Workspace (Docs, Sheets, Drive, Gmail, Meet), BigQuery, 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 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 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 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 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 LangGraph.