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 including data ingestion, document processing, and promoting generation.
Increase model serving layers and high-throughput data processing pipelines, employing advanced libraries to ensure ultra-low latency and efficient resource use.
Design and implement secure system architectures for all new AI products ensuring compliance with data governance and security policies.
Understand how to use Terraform for provisioning and manage Azure infrastructure-as-code.
Support automated and reproducible Continuous Integration/Continuous Deployment (CI/CD) pipelines.

Bachelor's Degree in Relevant Field or Equivalent Years of Relevant Experience.
Typically requires 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, regardless of the underlying cloud vendor.
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.

Health Insurance including Medical, Dental and Vision
401k
Paid Time off
Parental and Caregiver Leave
Flexible Work Schedule where you will work with your manager to enjoy a work schedule that can be flexible with your personal life.

Senior Agentic AI Architect

Key skills