Description

You will design enterprise-scale AI reference architectures spanning experience, agentic core, retrieval, orchestration, integration, models, data platform, and infrastructure layers. This role is on-site.

Responsibilities

• Design agentic and application architectures including agent runtimes, reasoning loops, tool calling, multi-agent orchestration, workflow routing, memory, and human-in-the-loop controls.
• Define AI guardrails and responsible AI controls, including content filtering, prompt-injection defense, PII redaction, policy enforcement, safety classifiers, red-teaming, and audit logging.
• Architect integration patterns using API gateways, service mesh, event streaming, connector catalogs, secure identity propagation, and protocol mediation like MCP and A2A.
• Manage model serving and lifecycle capabilities, including model registries, commercial and open-source hosting, inference infrastructure, fine-tuning, and continuous evaluation.
• Implement MLOps, LLMOps, and AgentOps practices for pipeline orchestration, CI/CD for models and agents, deployment, drift detection, and cost metering.

Required Skills

• 9–15+ years of overall technology experience with 5+ years in Solution, Enterprise, Data, Platform, or AI Architecture roles.
• Strong Azure architecture skills across landing zones, subscriptions, networking, private connectivity, identity management, and AI/data services.
• Deep understanding of predictive AI, generative AI, foundation models, agentic AI, RAG, vector/hybrid search, semantic layers, and knowledge graphs.
• Experience with on-premises architecture including data center hosting, virtualized infrastructure, GPU/accelerator capacity, and secure connectivity.
• Ability to design hybrid AI deployment patterns spanning Azure and on-premises environments, covering workload placement, data residency, and failover.
• Strong knowledge of enterprise data platform capabilities, including governed data products, feature/embedding stores, lineage, and security controls.
• Experience with infrastructure platforms including Kubernetes, autoscaling inference, secrets management, and observability.

Preferred Skills

• Experience delivering enterprise-scale AI platforms or AI-enabled transformation initiatives.
• Background working within regulated, security-conscious, or governance-driven environments.

Key Skills

Education

Bachelor's degree