Senior Solution AI Architect - Remote
Remote United States Full-time Senior Other
At a glance
Senior role at Zealogics.com. Remote, United States · full-time · $140,000–$145,000 base.
SalaryStated by Zealogics.com
$140,000 – $145,000
Base salary for this role, in USD per year, as published in the posting.
RoleOther
SenioritySenior
LocationUnited States
WorkplaceRemote
EmploymentFull-time
Base pay$140,000–$145,000
PostedSep 24, 2026 · 4w ago
Role brief
remoteroles summary, based on the employer's posting.
What you'll do
- Shape end-to-end AI systems for enterprise applications, then carry them from early concepts through production
- Choose how LLMs, retrieval, agents, embeddings, vector stores and prompts fit into each solution
- Set architecture patterns and roadmaps, and assess use cases to recommend models, platforms and frameworks
- Connect AI systems with business applications, APIs, databases and cloud environments
- Lead design reviews and proof-of-concepts while guiding teams on security, governance, privacy and performance
What you bring
- Extensive work in solution, enterprise or AI architecture, with hands-on design of generative AI and LLM systems
- Strong command of retrieval-augmented generation, agents, embeddings, vector databases, prompt design and LLM application architecture
- Practical experience with cloud AI services and Python, APIs, microservices, databases and cloud-native systems
- Background building secure, scalable enterprise applications, plus knowledge of MLOps or LLMOps, evaluation, monitoring and deployment
- Clear communication and technical leadership, including explaining AI concepts to technical and nontechnical audiences
Who this fits
This remote, full-time senior role suits an experienced architect who can lead AI design while staying hands-on. You’ll work with business stakeholders, engineering teams and senior leaders, and provide technical guidance to AI and engineering teams.
From the employer
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
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.
- 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.
- 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.
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OtherRemote$140k+
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