At a Glance
- Tasks: Lead the development of AI-powered digital products and transform customer experiences.
- Company: Join a leading tech firm driving innovation in AI and digital platforms.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic environment fostering innovation and collaboration across global teams.
- Why this job: Be at the forefront of AI technology and make a significant impact on global engineering teams.
- Qualifications: 20+ years in software engineering with leadership experience in large-scale projects.
The predicted salary is between 150000 - 200000 £ per year.
We are seeking a visionary Senior Vice President – Engineering to lead the next generation of AI-powered digital products and platforms. This role will drive the strategy, architecture, and execution of large-scale Agentic AI systems, transforming customer experiences, operational workflows, and engineering productivity through intelligent autonomous agents.
The ideal leader has successfully built and scaled 0→1 AI products from concept to production, with deep expertise in deploying Agentic AI solutions at enterprise scale. You will lead global engineering teams responsible for delivering AI-native products that serve millions of customers while modernizing legacy platforms into intelligent, autonomous systems.
Key Responsibilities- Agentic AI Strategy & Vision
- Define and execute a 3–5 year engineering and Agentic AI roadmap aligned with business objectives.
- Drive adoption of Agentic AI across customer journeys, service operations, commerce platforms, and engineering workflows.
- Establish a long-term vision for AI-native products powered by autonomous agents, orchestration frameworks, and LLM-driven decision systems.
- Partner with executive leadership to identify high-impact opportunities where Agentic AI can create measurable business value.
- Build Agentic AI Products (0→1 to Production)
- Lead the design, development, and production deployment of Agentic AI systems from ideation through enterprise-scale rollout.
- Build multi-agent workflows capable of planning, reasoning, tool usage, memory management, and autonomous execution.
- Drive implementation of LLM orchestration frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent platforms.
- Establish best practices for AI evaluations, guardrails, observability, governance, safety, and reliability.
- Own the complete lifecycle of AI systems including experimentation, validation, production deployment, monitoring, and continuous optimization.
- Engineering & Platform Leadership
- Lead engineering teams building customer-facing platforms, commerce ecosystems, CRM solutions, service applications, and AI-enabled experiences.
- Drive modernization of legacy platforms into cloud-native, API-first, AI-ready architectures.
- Ensure engineering excellence through scalable system design, automation, observability, and operational rigor.
- Guide teams in building highly available, secure, and resilient distributed systems.
- AI Platform & Infrastructure
- Build enterprise-grade AI platforms supporting model serving, vector databases, RAG pipelines, agent orchestration, and AI observability.
- Define standards for AI governance, model lifecycle management, prompt engineering, evaluation frameworks, and responsible AI practices.
- Establish scalable infrastructure supporting large-scale AI workloads and autonomous workflows.
- Lead adoption of AI engineering best practices across the organization.
- Executive Leadership & Business Impact
- Partner with CIOs, CPOs, and executive stakeholders to align technology investments with business priorities.
- Drive large-scale transformation initiatives delivering significant business impact through AI and automation.
- Influence product strategy through deep understanding of customer needs, competitive landscape, and emerging AI technologies.
- Represent the organization externally with customers, partners, investors, and industry leaders.
- Organization Building
- Lead, mentor, and scale high-performing global engineering organizations.
- Build strong leadership teams capable of driving innovation and execution at scale.
- Foster a culture of experimentation, ownership, engineering excellence, and AI-first thinking.
- Attract and retain world-class engineering and AI talent.
- 20+ years of software engineering experience with significant leadership responsibility.
- Proven experience leading large-scale global engineering organizations (500+ engineers preferred).
- Strong hands-on background in software architecture, distributed systems, cloud platforms, and enterprise-scale engineering.
- Demonstrated success building Agentic AI products from 0→1 and taking them into production environments.
- Deep expertise in: Agentic AI Architectures, Multi-Agent Systems, LLM Orchestration, RAG Architectures, AI Workflow Automation, Autonomous Decision Systems, Prompt Engineering & Evaluation Frameworks, AI Observability & Monitoring.
- Experience deploying production-grade AI systems serving large-scale customer or enterprise workloads.
- Strong understanding of AI governance, security, safety, compliance, and model lifecycle management.
- Experience driving AI adoption across customer experience, commerce, operations, or engineering productivity functions.
- Proven ability to influence executive stakeholders and drive enterprise-wide transformation initiatives.
- Strong track record of hiring, mentoring, and scaling high-performing engineering organizations.
- B2C, D2C, Consumer Internet, Digital Platforms, E-Commerce, Telecom, SaaS, or FinTech environments.
- Experience working with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent.
- Exposure to Voice AI, Conversational AI, AI Agents, Copilots, and Autonomous Workflow Systems.
- Experience building AI platforms supporting millions of users and high-volume transactions.
- Strong understanding of cloud-native technologies and modern platform engineering.
- Bachelor's or Master's Degree in Computer Science, Engineering, or related discipline.
- Establish a world-class Agentic AI engineering organization.
- Deliver multiple AI-native products from concept to production.
- Transform legacy workflows into autonomous AI-driven systems.
- Build scalable AI platforms enabling rapid innovation across the enterprise.
- Drive measurable business impact through AI-powered automation, productivity, and customer experience transformation.
Head of Technology (Germany Onsite) in England employer: Questhiring
As a leading employer in the technology sector, we offer an innovative work culture that fosters creativity and collaboration among our global teams. Our commitment to employee growth is evident through extensive training programs and opportunities to lead cutting-edge AI projects, all while working in vibrant locations like Gurgaon and Bangalore. Join us to be part of a transformative journey where your contributions will directly impact millions of customers and shape the future of AI-powered solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Technology (Germany Onsite) in England
✨Tip Number 1
Network like a pro! Get out there and connect with industry folks on LinkedIn or at events. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal website showcasing your projects, especially those related to AI and engineering. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to AI and engineering leadership. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Head of Technology (Germany Onsite) in England
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Head of Technology role. Highlight your experience with Agentic AI and large-scale engineering projects, as this will show us you’re the right fit for our vision.
Showcase Your Leadership Skills:We want to see how you've led teams in the past. Share specific examples of how you've built and scaled engineering organisations, especially those with 500+ engineers. This will help us understand your leadership style and impact.
Demonstrate Your Technical Expertise:Don’t hold back on your technical skills! Detail your hands-on experience with AI architectures, multi-agent systems, and cloud platforms. We’re looking for someone who can dive deep into the tech while also driving strategy.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Questhiring
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Agentic AI and related technologies. Be ready to discuss your experience with building AI products from the ground up, as well as any specific frameworks like LangGraph or CrewAI that you've worked with.
✨Showcase Leadership Experience
This role requires strong leadership skills, so be prepared to share examples of how you've successfully led large engineering teams. Highlight your experience in mentoring and scaling teams, and how you've driven innovation in previous roles.
✨Align with Business Objectives
Understand the company's business goals and be ready to discuss how your vision for AI can align with these objectives. Think about how you can drive measurable business value through AI adoption and transformation initiatives.
✨Prepare for Technical Questions
Expect in-depth technical questions about software architecture, distributed systems, and cloud platforms. Brush up on your knowledge of AI governance, safety, and compliance, as these are crucial for the role.
