Overview:Job Summary: Enterprise AI fails more often on architecture than on model quality. R2 Technologies is seeking an AI Solutions Architect to define how LLM and agentic systems are designed, integrated, secured, and scaled across client environments. You will own architecture decisions spanning model selection and routing, retrieval design, orchestration patterns, integration with existing enterprise systems, and the security and cost controls that make AI workloads viable in production. This is a hands-on architecture role that stays close to the code.
Key Responsibilities:- Define enterprise AI reference architectures covering LLM integration, RAG design, agent orchestration, and data flow across client systems.
- Lead model selection and routing strategy across providers, balancing accuracy, latency, and cost per transaction.
- Design integration patterns connecting AI services to existing enterprise applications, APIs, microservices, and data platforms.
- Architect cloud-native AI deployments on AWS, Azure, or GCP, addressing scalability, resilience, and performance optimization.
- Establish AI security and governance standards, including guardrails, data handling controls, observability, and auditability for regulated environments.
- Conduct design reviews, build proof-of-concepts, and provide technical recommendations to client stakeholders and engineering teams.
Qualifications:- 3 years of experience in AI/ML solution architecture, applied within a broader enterprise software architecture background.
- Strong hands-on experience with LLM platforms including Anthropic Claude, OpenAI, Google Gemini, or open-source models.
- Expertise in AI orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel, and RAG architecture with vector databases.
- Proficiency in Python, with working knowledge of Java, .NET, or Node.js in enterprise contexts.
- Proven experience designing REST APIs, microservices, and event-driven architectures at enterprise scale.
- Strong cloud architecture experience on Azure, AWS, or GCP, including containerization, IAM, and infrastructure-as-code.
Skills:AI Solution Architecture,LLM,RAG,LangChain,LangGraph,Python,Enterprise Integration,Cloud Architecture,Microservices
