Engineering Manager AI

Overview

As Engineering Manager (AI) within Advanced Analytics (DA3) in the Chief Data & AI Office at Allianz Partners, you will manage our AI engineering teams: engineers who build agent-based AI services and conversational/voice AI systems that integrate with our digital insurance products. The remit covers two delivery surfaces: agent-based AI services consumed by domain teams via API (and conforming to Core Backend client libraries / API conventions where applicable), and voice/conversational AI experiences for customer-facing and operational use cases.

You will own people management, performance, hiring, resourcing, and delivery leadership. Technical decisions stay with the senior engineers and technical leads in each team. Your role is to build the people structure, capacity, and ways of working that let those engineers ship applied AI into production. You'll partner with peer Engineering Managers on cross-team dependencies, with the AI Governance Review forum on AI compliance and ethics review, and with the Head of AI Platform & Engineering (HoP&E) as CAB chair on AI service change windows.

Key Responsibilities

• Manage and grow the AI teams: hiring, onboarding, performance management, career development, and 1:1s for ML/AI engineers, computational linguists, conversational AI engineers, and AI specialists embedded with delivery teams.

• Capacity-balance engineers across the agent and voice surfaces in response to demand from domain teams; coordinate with senior leadership on team sizing and skill mix.

• Coordinate the embedded-AI-specialist model with the backend Engineering Manager: agree how specialists join domain delivery, how their performance is reviewed, and how their work is balanced between embedded delivery and central capability building.

• Coach and develop the technical leads in both teams: support them as authorities on prompt engineering, agent design, NLU/NLP, and voice flow design while keeping standards consistent.

• Work with the AI Governance Review forum (the dedicated AI-ethics body in the hub operating model) on AI compliance reviews: model choices, data handling, bias review, and compliance attestations.

• Coordinate change windows for AI service rollouts through the HoP&E-chaired CAB; feed the change calendar to the Run & Change service layer.

• Help balance the agent and voice roadmaps: ensure investment is staged correctly across each surface and the hybrid use cases that span both.

• Coordinate with backend leadership on how AI services are consumed in production.

• Coordinate with frontend leadership on AI-driven UX patterns.

• Work with delivery leads on ceremonies, cross-team planning, and continuous improvement of delivery flow.