AI Architect

Job role- AI Architect/ Engineer

Location: Paramus, NJ / Hybrid(Locals or Nearby Only)

Full Time

AI Architect – Google AI & Generative Intelligence

Local NJ-based AI Architects with strong Google AI stack (Vertex AI, Gemini, ADK) and enterprise-scale Generative AI experience.

We are seeking a highly accomplished AI Architect with deep expertise in Google AI technologies and Generative AI to lead the design and implementation of enterprise-scale AI solutions. This role requires strong architectural vision, hands-on technical depth, and leadership in building production-grade AI systems leveraging LLMs, SLMs, and multi-agent frameworks .

The ideal candidate will drive AI strategy, define scalable architectures, and lead cross-functional teams in delivering cutting-edge AI-powered applications using the Google Cloud ecosystem , modern AI frameworks, and robust MLOps practices.

Key Responsibilities

1. AI Architecture & Strategy

· Define end-to-end AI/GenAI architecture for enterprise-grade applications.

· Establish best practices for LLM/SLM adoption, multi-agent systems, and RAG architectures .

· Drive AI platform strategy leveraging Google Cloud (Vertex AI, GKE, Cloud Run) .

· Lead architecture reviews, technical governance, and design standards.

2. LLM / SLM & Generative AI Solutions

· Architect solutions using commercial LLMs such as Gemini, GPT, and Claude .

· Design scalable systems using open-source models (Mixtral, Mistral, Gemma, Phi-3) .

· Define strategies for fine-tuning (LoRA, QLoRA, PEFT) and model optimization.

· Oversee model evaluation frameworks and benchmarking (HELM, lm-eval, RAGAS).

3. Google AI Ecosystem Leadership

· Lead adoption of:

o Vertex AI for model lifecycle management

o Google Agent Development Kit (ADK) for intelligent agents

o Google Workspace integrations (Docs, Sheets, Gmail, Drive, Meet)

· Architect solutions using BigQuery, Lakehouse, and Vector Databases .

4. AI Platform & MLOps Architecture

· Design scalable MLOps pipelines for training, deployment, and monitoring.

· Define CI/CD strategies for AI systems using GitHub Actions / GitLab CI .

· Establish observability frameworks using LangSmith, MLflow, Weights & Biases .

· Optimize infrastructure cost and performance across cloud and hybrid environments.

5. Multi-Agent Systems & AI Frameworks

· Architect complex workflows using:

o LangChain, LlamaIndex, LangGraph

o Semantic Kernel for multi-agent orchestration

· Design intelligent automation pipelines and agent collaboration patterns.

6. Data & RAG Architecture

· Design enterprise RAG pipelines using Vertex AI Vector DB, ChromaDB .

· Define data ingestion, transformation, and governance strategies.

· Architect semantic search and knowledge retrieval systems.

7. Application & Integration Architecture

· Define backend architecture using FastAPI / Node.js APIs .

· Architect API management and security using Apigee / MuleSoft .

· Guide frontend architecture using React / Angular for AI-driven applications.

8. Engineering Leadership

· Provide technical leadership and mentorship to AI/ML engineers.

· Collaborate with product, data, and engineering teams for solution delivery.

· Lead design documentation, architecture diagrams, and technical roadmaps.

· Ensure adherence to coding standards, testing, and quality frameworks.

9. Deployment & Infrastructure

· Architect deployments across:

o GCP (Vertex AI, GKE, Cloud Run)

o Hybrid and on-prem environments

o Edge AI use cases

· Ensure scalability, reliability, and security of AI systems.

10. AI Governance & Responsible AI

· Define frameworks for AI ethics, bias mitigation, and explainability .

· Establish governance for model lifecycle, monitoring, and compliance .

· Implement safeguards for hallucination detection and output validation.

Required Qualifications

· 12–18 years of software engineering experience.

· 7+ years in AI/ML with strong focus on Generative AI and LLMs .

· Deep expertise in Google AI ecosystem (Vertex AI, Gemini, ADK, AI Studio) .

· Strong experience in LLMs, SLMs, RAG, and multi-agent architectures .

· Proficiency in Python and familiarity with Node.js .

· Hands-on experience with MLOps, CI/CD, and cloud-native architecture (GCP) .

· Proven experience designing *…