AI Architect/AI Engineer – Generative & Agentic AI

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About the Role We are seeking an experienced hands-on AI Architect to lead the architecture, design, and delivery of enterprise-scale Generative and Agentic AI solutions. This is a hands-on architectural leadership role spanning system design, rapid proof-of-concept (POC) and MVP delivery, API-first solution architecture, and technical governance across our AI platform. The ideal candidate combines deep technical depth in LLMs, multi-agent orchestration, and RAG architecture with the ability to translate business needs into scalable, production-grade AI systems and to mentor engineering teams along the way.

Own end-to-end architecture for enterprise Generative AI and Agentic AI solutions, from concept through production. Lead rapid POC and MVP development to validate AI use cases and de-risk technical approaches before full build-out. Architect scalable AI platforms leveraging LLMs, RAG pipelines, vector databases, and multi-agent orchestration frameworks (LangGraph, AutoGen, Semantic Kernel). Design API-first architectures (REST/GraphQL) that expose AI capabilities to downstream applications and enterprise systems. Define technology selection, architecture standards, and best practices for prompt engineering, model evaluation, and AI governance / Responsible AI. Architect and guide MLOps/LLMOps practices for deployment, monitoring, and model/agent lifecycle management. Lead architecture reviews and present designs to executive sponsors and engineering teams; drive stakeholder alignment. Mentor AI engineers, set coding and architecture standards, and raise the technical bar across the team. Evaluate and select cloud-native AI services (Azure AI Foundry, Google Vertex AI), balancing scalability, cost, security, and performance. Our Tech Stack Databricks platform, Unity Catalog for governance, Delta Lake for data storage, Databricks Apps for hosting, and Databricks AI Gateway for model routing and governance.  Microsoft Azure, including Azure AI Foundry for model deployment and orchestration.  Multi-LLM provider access. Anthropic Claude, OpenAI (GPT & Codex), and other foundation models.

Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. 6+ years of overall IT experience spanning software engineering, cloud architecture, and/or AI/ML. 3+ years of hands-on architecture experience specifically in Generative AI / Agentic AI systems. Strong expertise in Python and modern AI development frameworks. Demonstrated experience architecting solutions with LLMs (OpenAI, Claude, Gemini, Llama, or open-weight models). Deep understanding of RAG architectures, vector databases (Pinecone, FAISS, Databricks Vector Databases, pgvector), and embedding models. Experience architecting on at least one major cloud platform (Azure, AWS, or GCP), including native AI services (Azure AI Foundry / Azure OpenAI, AWS Bedrock, Google Vertex AI). Proven experience with MLOps/LLMOps: CI/CD, containerization (Docker/Kubernetes), observability, and evaluation frameworks. Strong grounding in AI governance, security, compliance, and Responsible AI practices. Excellent communication skills, with the ability to present architecture to both executives and engineers.

Experience designing state management and persistent memory for long-running autonomous agents. Familiarity with Model Context Protocol (MCP) and emerging AI agent ecosystems. Experience with AI observability / evaluation tooling (LangSmith, Ragas, Langfuse, or custom eval harnesses). Prior consulting,