AI Technical Lead

Overview

In this role, you will lead the technical delivery of enterprise AI systems on a Microsoft-first stack, shaping AI capabilities across Teva’s digital and data platforms. You’ll work with cross-functional teams to design, build, and operate production-grade AI solutions that scale globally while enforcing governance, security, and Responsible AI practices. Your leadership will blend hands-on engineering with strategic direction to accelerate innovation and modernize decision making.

Pay / Benefits

• generous annual leave
• reward plans
• flexible working schedules
• tailored health support
• career development via Twist
• internal growth opportunities

Responsibilities

• Own AI engineering activities within the DADAI delivery factory
• Lead design, build, and operation of enterprise AI solutions on Azure-based stack
• Remain hands-on: review architecture, build POC, troubleshoot, guide production hardening
• Define and enforce engineering standards for AI delivery (security, privacy, Responsible AI)
• Collaborate with architects, platform security, and governance teams to ensure scalable, compliant AI solutions
• Ensure AI solutions are aligned to business needs across regions and delivery models

Key requirements

• 7+ years leading large engineering teams in enterprise environments
• 10+ years software engineering experience in modern Microsoft cloud environments
• 2+ years delivering complex GenAI/agentic solutions on Microsoft tech (Azure OpenAI, Azure AI Foundry, Copilot Studio, RAG)
• Strong Azure engineering background (Azure Functions, App Services, AKS, API Management, Entra, CI/CD, monitoring)
• 10+ years hands-on technical leadership: build POCs/MVPs, code/architecture reviews, production issue troubleshooting
• 5+ years in regulated environments with strong security, privacy, governance, and Responsible AI controls
• BSc/BA in Computer Science, Software Engineering, Information Systems; Azure or AI certifications a plus

• Strong communication across diverse stakeholders
• Cross-functional collaboration in global delivery environments
• Problem solving across prompts, models, orchestration, performance and cost
• Azure OpenAI, Azure AI Foundry, Copilot Studio, Semantic Kernel, Prompt Flow
• Azure Functions, App Services, AKS, API Management, Entra, CI/CD, monitoring
• Azure DevOps, GitHub Enterprise, Azure Machine Learning, observability

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