At a Glance
- Tasks: Lead AI engineering teams to develop innovative agent-based and conversational AI services.
- Company: Join Allianz Partners, a trusted leader in insurance and asset management.
- Benefits: Enjoy competitive salary, inclusive culture, and opportunities for career growth.
- Other info: Collaborative environment focused on innovation and ethical AI practices.
- Why this job: Make a real impact in AI while shaping the future of digital insurance.
- Qualifications: 8+ years in engineering with 3+ years in people management, especially in AI.
The predicted salary is between 80000 - 100000 £ per year.
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 (Ho P&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 Ho P&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.
- Run hiring loops: design interview rubrics for ML/AI engineers, computational linguists, conversational AI engineers, and embedded AI specialists aligned with the team\'s applied-AI delivery model.
- Required Experience And Skills
- 8+ years engineering experience with at least 3 years in a people-management role leading applied AI, ML, or conversational AI delivery teams.
- Track record managing 6 to 15 engineers across at least two distinct teams or specialisations (e. g., ML engineering and conversational/voice AI).
- Strong technical literacy in the AI stack, enough to mentor and challenge but not to override technical leads:
- LLM-based agent systems: prompt engineering, agent design patterns, evaluation, retrieval augmentation.
- Voice and conversational AI platforms: NLU/NLP system design, speech pipeline integration, dialogue management.
- Production deployment of AI services on Kubernetes: API design, observability, latency and cost control.
- Embedded-specialist delivery models: placing specialists into product teams without losing central capability ownership.
- Experience running structured hiring at scale for AI roles: rubric-based interviews, calibration, and onboarding programmes.
- Experience with formal performance management cycles, career frameworks, and compensation calibration.
- Comfortable working with formal AI governance and ethics review processes; familiarity with AI compliance requirements in regulated industries.
- Demonstrated ability to coordinate across organisational boundaries: peer Engineering Managers, governance, backend and frontend delivery teams, and external vendors.
- Ways of Working
- Leads through coaching, not directing: defers technical authority to senior engineers and technical leads.
- Comfortable in agile, iterative delivery environments with a clear bias for unblocking the team over centralising decisions.
- Pragmatic about applied AI: focused on shipping AI capabilities into production for measurable business outcomes, not on research for its own sake.
- Clear communicator across global, cross-functional stakeholders; able to translate AI capability and reliability into business impact for non-technical audiences.
- Pragmatic adopter of AI-assisted developer tools (e. g., Git Hub Copilot, Claude Code) and supports the team in integrating them into daily delivery.
- Nice to Have
- Experience leading distributed AI delivery teams.
- Background in voice or conversational AI at production scale (IVR replacement, contact-centre automation, voice-first product experiences).
- Experience operating an embedded-specialist model alongside a central capability team.
- Experience with AI governance frameworks: model cards, bias audits, regulatory attestations.
- Insurance or financial services domain familiarity (claims, policy, payments).
- Experience in regulated industries (insurance, finance, healthcare) where compliance, audit, and access control are part of standard delivery practice.
Allianz Group is one of the most trusted insurance and asset management companies in the world.
Caring for our employees, their ambitions, dreams and challenges is what makes us a unique employer.
We are united by a shared commitment: to put our customers first and at the center of everything we do.
Their needs inspire our thinking and guide our actions.
At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all.
The foundation for this is our inclusive workplace, where people and performance both matter, and where integrity, fairness, inclusion and trust are at the heart of our culture.
We therefore welcome applications regardless of race, ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations.
Join us.
Let\'s care for tomorrow.
Note
Having different strengths, experiences, perspectives and approaches is an integral part of Allianz‘s company culture.
One means to achieve this is a regular rotation of Allianz employees across functions, Allianz entities and geographies.
Therefore, Allianz expects from its employees a general openness and a high motivation to regularly change positions and collect experiences across Allianz Group.
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Engineering Manager AI in Croydon employer: Allianz Partners
Allianz Partners is an exceptional employer, offering a dynamic work environment in Budock Water where experienced vehicle technicians can thrive. With competitive pay, including a base salary of up to £41,200 and bonuses, employees benefit from a strong focus on professional growth, flexible working arrangements, and a commitment to customer care and safety. Join a team that values your skills and provides opportunities for meaningful contributions in roadside assistance.
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Manager AI in Croydon
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Allianz Partners or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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We think you need these skills to ace Engineering Manager AI in Croydon
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Allianz Partners.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Allianz Partners and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Allianz Partners
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Allianz Partners uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
