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Senior AI Engineer – Google AI & Generative Intelligence

Job in Paramus, Bergen County, New Jersey, 07653, USA
Listing for: Eclaro
Full Time position
Listed on 2026-06-04
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Senior AI Engineer - Google AI & Generative Intelligence Job Number: 26-00855 Ready for a rewarding opportunity in the Financial Services Industry? ECLARO is looking for a Senior AI Engineer - Google AI & Generative Intelligence for our client in Paramus, NJ. ECLARO's client is a market-leading insurance company, providing property, casualty, and specialty insurance services within the United States.

If you’re up to the challenge, then take a chance at this rewarding opportunity!

Position Overview:

A highly experienced Senior AI Engineer with deep expertise in Google AI technologies, Generative AI. Brings 10–15 years of broad software engineering experience, with the last 4 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.

Responsibilities:
Large & Small Language Model 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. Work with open-source/self-hosted LLMs including Mixtral (Mistral AI). Architect and implement SLM-based solutions using lightweight models such as Phi-3 (Microsoft), Gemma (Google), and Mistral for resource-constrained environments. Lead fine-tuning and customization of models using Vertex AI Tuning, Hugging Face Transformers, and parameter-efficient fine-tuning (PEFT) methods including LoRA and QLoRA.

Apply training frameworks such as PyTorch, Tensor Flow, or JAX for model experimentation and development. Generate synthetic data and evaluate models using HELM, lm-evaluation-harness, and custom benchmarks. 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 GKE (Google Kubernetes Engine) for container orchestration Cloud Run for serverless deployment Cloud Functions for event-driven AI tasks 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. Design UI/UX prototypes in Figma for AI-powered application interfaces. Manage project delivery and sprint planning using Jira. Oversee data preparation and management: cleaning, transforming, and organizing data for AI/ML workflows. Conduct data analysis using Jupyter Notebooks and pandas for exploration and preprocessing.

Leverage Hugging Face Model Hub for model comparison, selection, and download. Development Frameworks & Tools:
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. Deploy models locally with Ollama or at scale with vLLM for efficient inference. Track experiments, metrics, and results with MLflow or Weights & Biases. 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 Chroma

DB. 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:
Build modern user interfaces using React or Angular. Utilize Material-UI for consistent,…
Position Requirements
10+ Years work experience
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