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Selected role

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

NavitasPartners Paramus, NJ, US

Senior Full-time

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

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