Job Description: AI Architect (Agentic AI) — 10+ YearsRole Summary
We are seeking a highly experienced AI Architect with a strong foundation in .NET enterprise architecture(10+ years) and hands‑on capability in Python and Agentic AI systems.
The candidate will lead the architecture and technical direction for building cloud‑native, scalable, secure, and observable AI solutions on Microsoft Azure, with emphasis on Azure App Services, microservices, system integration, and CI/CD automation using Terraform.
Key Responsibilities
- Architect and design cloud‑native solutions using .NET and microservices architecture with modern integration patterns.
- Lead architecture reviews and ensure consistency with scalability, resiliency, performance, and maintainability principles.
- Design and guide implementation using Azure App Services and broader Azure platform services as needed.
- Ensure cloud architecture covers security, identity, networking, governance, and operational excellence.
- Partner with DevOps/Platform teams to implement and optimize CI/CD pipelines, deployment strategies, and environment automation.
- Drive Infrastructure as Code (IaC) using Terraform templates for repeatable and compliant deployments.
- Own the approach for system integration, API strategy, and service contracts across internal/external systems.
- Ensure robust patterns for API reliability, versioning, backward compatibility, and integration resilience (timeouts, retries, circuit breakers).
- Define observability standards for distributed systems: logs, traces, metrics, and operational dashboards.
- Drive reliability practices across microservices and AI components (resiliency, fallbacks, monitoring, runbooks).
- Define and drive end‑to‑end architecture for Agentic AI solutions including orchestration patterns, tool/function calling, and guardrails.
- Translate business problems into agent workflows, capability decomposition, and measurable success criteria.
- Establish architectural standards for prompting strategy, agent memory/context handling, and evaluation approach (quality, safety, reliability).
- Mentor engineers and guide best practices through design reviews, reference implementations, and enablement sessions.
- Collaborate with product, engineering, and stakeholders to align architecture with roadmap and delivery milestones.
Required Qualifications (Must‑Have)
- 10+ years overall experience in software engineering / architecture with strong enterprise .NET background.
- Experience designing or implementing Agentic AI systems (agents, orchestration, tools, context, guardrails).
- Strong experience with Azure App Services and cloud‑native design.
- Strong experience in CI/CD and Infrastructure as Code using Terraform.
- Proven expertise in microservices architecture and system integration.
Preferred / Nice‑to‑Have
- Exposure in Python (building services, integrations, orchestration utilities, or AI pipelines).
- Experience with event‑driven architecture, messaging, and async processing patterns on Azure.
- Knowledge of modern architectural styles/patterns (e.g., DDD, orchestration patterns, API gateways).
- Experience with Azure monitoring/observability tools and production operations.
- Exposure to secure cloud design (secrets management, identity, governance).
Core Competencies
- Architecture thinking, engineering excellence, and strong stakeholder communication
- Ability to simplify complex systems and establish pragmatic standards
Strong ownership mindset across design build- run (operational readiness)
agentic ai,generative ai,large language model,api integration,python,langgraph,model deployment,prompt engineering
