Senior AI Engineer – Google AI & Generative Intelligence - 26-05877

Senior AI Engineer – Google AI & Generative Intelligence

Job Title: Senior AI Engineer – Google AI & Generative Intelligence Location: Paramus, New Jersey (Hybrid) Duration: 6 Months Employment Type: Contract-to-Hire

Position Overview

We are seeking a highly experienced Senior AI Engineer with strong expertise in Google AI technologies, Generative AI, and cloud-native AI application development. The ideal candidate will bring 10–15 years of software engineering experience, including 5+ years focused on Artificial Generative Intelligence, building scalable AI systems, LLM/SLM applications, RAG architectures, and multi-agent solutions in production environments.

This role requires deep hands-on experience with the Google AI ecosystem including Gemini, Vertex AI, Google Agent Development Kit (ADK), Google AI Studio, and Google Workspace integrations.

Key Responsibilities

Large & Small Language Model Engineering

• Design, develop, and deploy AI agents leveraging commercial LLMs including:

• Gemini (Google)

• GPT (OpenAI)

• Claude Sonnet (Anthropic)

• Work with open-source and self-hosted LLMs such as:

• Mixtral (Mistral AI)

• Build lightweight SLM-based solutions using:

• Phi-3

• Gemma

• Mistral

• Fine-tune and customize models using:

• Vertex AI Tuning

• Hugging Face Transformers

• PEFT methods including LoRA and QLoRA

• Utilize frameworks such as:

• PyTorch

• TensorFlow

• JAX

• Perform synthetic data generation and model evaluations using:

• HELM

• lm-evaluation-harness

• Custom benchmarking frameworks

Google AI & Workspace Integration

• Design AI-powered workflows integrated with:

• Google Workspace

• Google Docs

• Sheets

• Drive

• Gmail

• Meet

• BigQuery

• Lakehouse platforms

• Develop intelligent AI agents using Google Agent Development Kit (ADK)

• Utilize:

• Google AI Studio

• VS Code

• Work extensively with Google Cloud Platform (GCP) services:

• Vertex AI

• GKE (Google Kubernetes Engine)

• Cloud Run

• Cloud Functions

• Vertex AI Vector Databases

AI Solution Design & Planning

• Lead requirements gathering and technical documentation using Confluence

• Create AI workflows and system architecture diagrams using Lucidchart

• Design UI/UX prototypes using Figma

• Manage Agile sprint planning and delivery using Jira

• Prepare, clean, and organize enterprise datasets for AI/ML workflows

• Conduct data analysis using Jupyter Notebooks and pandas

• Utilize Hugging Face Model Hub for model research and selection

Development Frameworks & AI Tooling

• Build orchestration pipelines using:

• LangChain

• LlamaIndex

• LangGraph

• Develop multi-agent AI systems using:

• Semantic Kernel

• LangGraph

• Manage prompt engineering and observability using:

• LangSmith

• PromptLayer

• Deploy models locally using Ollama and at scale using vLLM

• Track experiments using:

• MLflow

• Weights & Biases

• Manage source control with Git

Vector Databases & RAG Architecture

• Build Retrieval-Augmented Generation (RAG) systems using:

• Vertex AI Vector DB

• ChromaDB

• Design enterprise semantic search and knowledge retrieval architectures

Backend Development

• Develop scalable RESTful APIs using:

• FastAPI (Python)

• Express.js (Node.js)

• Manage APIs using:

• MuleSoft

• Apigee

Frontend Development

• Develop modern AI-driven user interfaces using:

• React

• Angular

• Material-UI

• Collaborate on UI/UX workflows and prototyping using Figma

Testing, Quality & Observability

• Perform LLM and RAG evaluations using:

• RAGAS

• DeepEval

• LangSmith Evaluators

• Create unit tests using pytest

• Monitor model performance and hallucination detection

• Track AI infrastructure costs using:

• OpenMeter

• Custom dashboards

Deployment & Infrastructure

• Deploy AI systems using:

• Kubernetes

• Google GKE

• Build CI/CD pipelines using:

• GitHub Actions

• GitLab CI

• Support:

• Cloud deployments

• Hybrid deployments

• Edge AI inference environments

Required Qualifications

• 10–15 years of overall software engineering experience

• 5+ years of hands-on Generative AI experience

• Strong expertise with:

• Gemini

• Vertex AI

• Google ADK

• Google AI Studio

• Google Workspace integrations

• Strong Python development experience

• Familiarity with Node.js

• Experience with:

• RAG systems

• Multi-agent AI architectures

• LLM/SLM fine-tuning

• LoRA / QLoRA / PEFT

• AI evaluation frameworks

• Strong cloud-native development experience on GCP

• Experience with MLOps and AI CI/CD pipelines

Preferred Qualifications

• Google Cloud certifications such as:

• Professional ML Engineer

• Professional Cloud Architect

• Experience contributing to open-source AI/ML projects

• Experience with edge AI and hybrid cloud deployments

• Experience building synthetic data generation pipelines

• Prior mentoring or leadership experience within AI/ML teams

For more details reach at resumes@navitassols.com