AI Technical Lead

Overview

In this role, you will lead the technical delivery of production-grade AI systems across Teva’s enterprise data, analytics, and AI landscape. You’ll set engineering direction on a Microsoft-first stack, delivering scalable AI capabilities with strong governance and security. You’ll collaborate with architecture, security, privacy, and governance teams to enable compliant, auditable AI solutions globally. This position offers hands-on leadership in a fast-paced, factory-like delivery environment that blends startup pace with enterprise discipline.

Pay / Benefits

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

Responsibilities

• Own all AI engineering activities within the DADAI delivery factory
• Lead design, build, and operation of enterprise AI solutions on a Microsoft-first stack (Azure OpenAI, Azure AI Foundry, Copilot Studio, Semantic Kernel)
• Review architecture and code, build proofs of concept, troubleshoot issues, guide production hardening
• Define and enforce engineering standards for AI delivery (security, privacy, Responsible AI, release controls)
• Collaborate with architects, platform teams, security, and stakeholders to ensure scalable, compliant AI solutions

Key requirements

• 7+ years leading and developing large engineering teams in a complex enterprise environment with people management
• 10+ years in software engineering, hands-on design and delivery of apps/APIs in a modern Microsoft cloud environment
• 2+ years delivering complex enterprise GenAI/agentic solutions on Microsoft technologies (Azure OpenAI, Azure AI Foundry, Copilot Studio, RAG)
• Strong Azure background (Azure Functions, App Services, AKS, API Management, Entra, CI/CD, monitoring, production support)
• 10+ years of hands-on technical leadership building POCs/MVPs/production apps, reviewing code and architecture
• 5+ years in enterprise or regulated environments with strong security, privacy, governance, Responsible AI controls
• BSc/BA in Computer Science, Software Engineering, Information Systems; Azure or AI certifications are a plus

• Strong communication across cross-functional teams
• Stakeholder management across architecture, security, delivery, and business teams
• Problem-solving across prompts, models, retrieval, orchestration, performance, and cost
• Azure OpenAI, Azure AI Foundry, Copilot Studio, Semantic Kernel, Prompt Flow
• Azure Functions, App Services, AKS, API Management, Logic Apps, Event Grid, Service Bus
• Azure DevOps, GitHub Enterprise, Azure Machine Learning, CI/CD, observability

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