Description

You design and deliver enterprise-scale AI reference architectures spanning experience, agentic core, retrieval, orchestration, integration, models, data platforms, and infrastructure layers.

This role is on-site.

Responsibilities

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

Required Skills

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

Preferred Skills

• Experience working within regulated, security-conscious, or governance-driven environments.
• Knowledge of infrastructure capabilities including autoscaling inference, isolated networks, hardened images, and vulnerability scanning.

Key Skills

Education

Bachelor's degree