System Architect (Azure)

Location: Netanya, Israel; onsite

Company

hirify.global develops responsible AI and an AI-powered Market Model for demand prediction and decision intelligence, with hirify.global Labs building an agentic solution for mid-market customers inside major enterprise-cloud, CRM, and productivity platforms.

What you will do

• Translate complex research assumptions, mathematical models, and decisioning methodologies into clean, self-service products with the Chief AI Officer.
• Design and own a scalable, cloud-native Azure architecture covering services, data flows, model serving, and the end-to-end decision pipeline.
• Lead the coding, make build-versus-buy decisions, write core code, and guide engineers by design and example without direct people management.
• Establish a fully agentic SDLC with AI coding agents, tooling, guardrails, code review, and CI gates.
• Build the greenfield Azure environment on a Kubernetes-native, Everything-as-Code foundation using IaC, GitOps, and CI/CD, including subscriptions, networking, and environments.
• Design integrations with enterprise-cloud, CRM, productivity, agent, and data platforms; ship the POC end to end and harden it toward a production-grade self-service GA platform.

Requirements

• 10+ years of software engineering experience with extensive hands-on production experience architecting, shipping, and running large-scale cloud-native systems.
• Hands-on architecture and coding experience; strong Python skills and the ability to own services from design through production.
• Kubernetes-native experience with declarative systems, controllers and operators, Docker, and Everything-as-Code discipline using Terraform and Helm.
• GitOps experience with ArgoCD or a similar tool and a defined, CI-gated SDLC.
• Production-first engineering practices covering reliability, observability, recoverability, SLOs, alerting, and blameless postmortems.
• Hands-on Azure experience at production scale is required. Azure is the sole cloud and the environment is being built from zero.
• Experience designing production systems for ML and data-science workloads, including model serving, feature or data pipelines, and inference at scale.
• Experience driving real work through AI coding agents and a clear approach to running a fully agentic SDLC safely.
• Fluent English for cross-team collaboration and technical documentation; ability to work effectively in an ambiguous, high-ownership, flat-team environment.

Nice to have

• Azure AI tooling experience, including AI Foundry, Copilot, or Fabric, and integrations across CRM, sales, productivity, or data platforms.
• Data-engineering and data-science experience, including data pipelines, feature engineering, and data-quality reasoning.
• Pricing systems, decision-support or decisioning systems, forecasting, or optimization experience.
• Platform-engineering experience building secure, automated, self-service pathways for engineers.
• Experience taking a 0-to-1 product from POC to GA.
• MLOps or LLMOps and pipeline orchestration experience with Airflow, Dagster, Kedro, Ray, or Kubeflow.
• Policy-as-code, supply-chain or CI security, OPA/Conftest, Kyverno, SLO or error-budget practices, and DORA-based delivery experience.
• Go or Bash experience.

Culture & Benefits

• Small, flat, deliberately senior team with high trust, direct ownership, and no management layers or unnecessary ceremony.
• Greenfield environment with POC-speed delivery and decisions that can ship quickly.
• Hands-on collaboration with Microsoft teams while establishing the Azure foundation.
• Engineering culture focused on quality, observability, cost awareness, automation, and agent-driven development.