AI Architect - Paramus, NJ​/Hybrid; local

AI Architect

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.

• 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.
• 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).
• Lead adoption of:
• Vertex AI for model lifecycle management
• Google Agent Development Kit (ADK) for intelligent agents
• Google Workspace integrations (Docs, Sheets, Gmail, Drive, Meet)
• Architect solutions using Big Query, Lakehouse, and Vector Databases.
• Design scalable MLOps pipelines for training, deployment, and monitoring.
• Define CI/CD strategies for AI systems using Git Hub Actions / Git Lab CI.
• Establish observability frameworks using Lang Smith, MLflow, Weights & Biases.
• Optimize infrastructure cost and performance across cloud and hybrid environments.
• Architect complex workflows using:
• Lang Chain, Llama Index, Lang Graph
• Semantic Kernel for multi-agent orchestration
• Design intelligent automation pipelines and agent collaboration patterns.
• Design enterprise RAG pipelines using Vertex AI Vector DB, ChromaDB.
• Define data ingestion, transformation, and governance strategies.
• Architect semantic search and knowledge retrieval systems.
• Define backend architecture using FastAPI / Node.js APIs.
• Architect API management and security using Apigee / Mule Soft.
• Guide frontend architecture using React / Angular for AI-driven applications.
• 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.
• Architect deployments across:
• GCP (Vertex AI, GKE, Cloud Run)
• Hybrid and on-prem environments
• Edge AI use cases
• Ensure scalability, reliability, and security of AI systems.
• 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.

• 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 scalable, production-grade AI systems.

• Google Cloud Certifications (Professional ML Engineer / Cloud Architect).
• Experience contributing to open-source AI/ML projects.
• Expertise in edge AI and hybrid cloud deployments.
• Experience building enterprise AI platforms or COEs.
• Strong leadership experience mentoring and scaling AI teams

• Generative AI (LLMs, SLMs, RAG, Agents)
• Google Cloud AI Stack (Vertex AI, Gemini, ADK)
• AI Frameworks (Lang Chain, Lang Graph, Llama Index, Semantic Kernel)
• MLOps & Observability (MLflow, W&B, Lang Smith)
• Cloud & Infrastructure (GCP, Kubernetes, Serverless)
• Backend & APIs (FastAPI, Node.js, Apigee)
• Data & Vector DBs (Big Query, ChromaDB, Vector Search)

Regards

Jaya Kushwaha

Associate Manager – Recruitment

Email:

USG Inc. | Vistara Solutions Inc.