Senior Solution AI Architect - Remote

zealogicsllc; New Jersey; Remote; USD 140,000 - 145,000; Full time

Job summary

zealogicsllc is seeking a hands-on technology leader with deep expertise in Generative AI, LLMs, AI agents, and enterprise solution architecture to translate business requirements into scalable, secure AI solutions.

The role focuses on architecting end-to-end AI programs, evaluating models and platforms, and driving POCs through production while ensuring AI governance and data privacy.

Qualifications

• Extensive experience in Solution Architecture, Enterprise Architecture, or AI Architecture.
• Strong hands-on experience designing Generative AI and LLM-based solutions.
• Deep understanding of RAG, AI agents, embeddings, vector databases, and LLM app architecture.
• Experience with cloud AI platforms such as Azure AI, AWS, or Google Cloud AI.
• Strong experience with Python, APIs, microservices, databases, and cloud-native architecture.
• Knowledge of MLOps/LLMOps, model evaluation, monitoring, and deployment.
• Strong understanding of AI governance, responsible AI, security, and data privacy.

Responsibilities

• Architect and lead end-to-end AI and Generative AI solutions across enterprise apps.
• Design solutions leveraging LLMs, RAG, AI agents, embeddings, and prompts.
• Define enterprise AI architecture standards and roadmaps.
• Evaluate AI use cases and recommend models, platforms, and architecture approaches.
• Integrate AI solutions with enterprise apps, APIs, databases, and cloud platforms.
• Lead architecture reviews, technical design sessions, and AI POCs.
• Translate business needs into technical solutions with stakeholders and engineering teams.
• Establish best practices for AI security, governance, scalability, and performance.
• Provide technical leadership and mentorship to engineering teams.
• Drive AI solutions from concept to production.

Skills

Solution Architecture

Enterprise Architecture

AI Architecture

Generative AI

LLMs

RAG

AI agents

Embeddings

Vector databases

Prompt engineering

Cloud platforms

Python

APIs & microservices

MLOps/LLMOps

AI governance & data privacy

Tools

Azure OpenAI

AWS Cloud AI

Google Cloud AI

Job description

The ideal candidate will have deep expertise in Generative AI, Large Language Models (LLMs), AI agents, RAG, cloud AI platforms, and enterprise solution architecture. This position requires a hands-on technology leader who can translate business requirements into scalable, secure, and production-ready AI solutions.

Key Responsibilities

• Architect and lead end-to-end AI and Generative AI solutions across enterprise applications.
• Design solutions leveraging LLMs, RAG, AI agents, embeddings, vector databases, and prompt engineering.
• Define enterprise AI architecture standards, patterns, and technology roadmaps.
• Evaluate AI use cases and recommend appropriate models, platforms, frameworks, and architecture approaches.
• Integrate AI solutions with enterprise applications, APIs, databases, and cloud platforms.
• Lead architecture reviews, technical design sessions, and AI proof-of-concepts.
• Work closely with business stakeholders, engineering teams, and senior leadership to translate business needs into technical solutions.
• Establish best practices for AI security, governance, responsible AI, data privacy, scalability, and performance.
• Provide technical leadership and mentorship to engineering and AI development teams.
• Drive AI solutions from initial concept and POC through production implementation.

Required Qualifications

• Extensive experience in Solution Architecture, Enterprise Architecture, or AI Architecture.
• Strong hands-on experience designing Generative AI and LLM-based solutions.
• Deep understanding of RAG, AI agents, embeddings, vector databases, prompt engineering, and LLM application architecture.
• Experience with cloud AI platforms such as Azure AI / Azure OpenAI, AWS, or Google Cloud AI.
• Strong experience with Python, APIs, microservices, databases, and cloud-native architecture.
• Experience architecting secure and scalable enterprise applications.
• Knowledge of MLOps/LLMOps, model evaluation, monitoring, and deployment.
• Strong understanding of AI governance, responsible AI, security, and data privacy.
• Excellent communication, technical leadership, and stakeholder-management skills.
• Ability to communicate complex AI concepts to both technical and non-technical stakeholders.

Preferred Qualifications

• Experience building enterprise AI copilots, intelligent assistants, and agentic AI solutions.
• Experience taking GenAI solutions from POC to enterprise production environments.
• Knowledge of enterprise search and vector database technologies.
• Experience driving AI technology strategy and architecture decisions.
• Relevant Cloud, AI, or Solution Architecture certifications are preferred.

Rate range -$140k-$145k