Senior Agentic AI Architect – Engineer

Responsibilities

• Architect AI Agents that use Tools and Skills including instantiation of MCP clients and servers
• Architect scalable end-to-end Retrieval-Augmented Generation (RAG) pipelines
• Increase model serving layers and high-throughput data processing pipelines
• Designing and implementing secure system architectures for all new AI products
• Understand how to use Terraform for provisioning and manage Azure infrastructure-as-code
• Understand centralized observability to support automated and reproducible CI/CD pipelines

• Bachelor's Degree in Relevant Field or Equivalent Years of Relevant Experience
• 8+ years of relevant work experience
• Expert-level proficiency in Python and SQL
• Hands‑on experience developing and deploying Generative AI solutions, RAG pipelines, and multi‑agent frameworks
• 5+ years of experience with major cloud platforms, specifically Microsoft Azure, AWS, or Google Cloud Platform (GCP)
• 1+ years of experience working with and integrating with ERP solutions like IFS Cloud
• 1+ years of experience working with and managing partners through end‑to‑end solution design through delivery
• Worked on core MLOps and orchestration tools, including Docker, Airflow
• Worked with vector search platforms like Azure Cosmos DB for PostgreSQL, Redis, Azure AI Search, or pgvector/Mongo Atlas
• Familiarity with classical ML modeling techniques such as Causal Inference, Matrix Factorization, XGBoost
• Familiarity with Scaled Agile Framework (SAFe) methodologies.

• Python
• SQL
• Generative AI
• Retrieval-Augmented Generation (RAG)
• MLOps
• Docker
• Airflow
• Causal Inference
• Matrix Factorization
• XGBoost

• Bachelor's Degree in Relevant Field