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For Companies At a Glance
- Tasks: Lead a squad to build and scale AI-enabled solutions for major organisations.
- Company: Join EY, a leader in engineering-led AI and innovation.
- Benefits: Competitive salary, flexible hybrid working, and continuous learning opportunities.
- Other info: Be part of a collaborative culture with excellent career growth potential.
- Why this job: Shape the future of AI while making a real impact in diverse sectors.
- Qualifications: Expertise in software engineering, AI/ML, and cloud architecture required.
The predicted salary is between 80000 - 100000 ÂŁ per year.
At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
Why EY
EY is investing in engineering-led AI at scale. EY has been selected for the inaugural Frontier Firm AI Initiative — a collaboration between Microsoft and Harvard’s Digital Data Design Institute — recognising EY’s leadership in shaping enterprise-grade human–AI operating models. In parallel, EY is expanding its collaboration with OpenAI and Microsoft, bringing advanced AI capabilities to clients through Microsoft’s secure Azure OpenAI Service. Joining this team means being part of a growing engineering capability focused on building production-grade AI systems for major organisations across sectors.
The opportunity
Organisations are moving rapidly from AI experimentation to operational adoption. However, many struggle to translate ideas into secure, scalable and reliable production solutions. Applied AI Engineering focuses on the hands-on engineering required to build, test and support these systems—aligned to EY platform patterns, responsible‑AI guardrails, and governance. As an Applied AI Engineering Squad Lead, you will act as a senior engineering and product leader, guiding squad teams in building and scaling AI-enabled solutions. You will shape the technical direction, product vision and delivery approach for applied AI systems across engagements, ensuring that solutions deliver measurable value while meeting enterprise standards for reliability, security and responsible AI.
You will lead a 4-7 person Applied AI Engineering squad, bringing together engineers, architects and designers to deliver AI systems. You will ensure technical coherence across delivery, establish strong engineering practices and help organisations successfully operationalise AI capabilities. As part of the Applied AI Engineering Academy, you will both deepen and share advanced engineering capabilities across the team. The academy supports continued development in areas such as AI system architecture, scalable engineering patterns and responsible AI practices, while also providing a platform to mentor engineers, contribute reusable patterns and help shape the technical standards of the capability. Through collaborative engineering challenges, knowledge sharing and capability initiatives, you will play an active role in strengthening how Applied AI Engineering solutions are designed, delivered and scaled across engagements. In this lead role, you will operate at the intersection of engineering leadership, product strategy and client engagement, shaping how AI-enabled systems are designed, delivered and scaled in complex enterprise environments.
What you’ll do
- Client-facing engineering & delivery: Define the strategic direction for the squad, including roadmap priorities, solution scope and delivery outcomes. Partner with senior client stakeholders to shape AI solution vision, adoption strategies and value realisation. Drive delivery across complex programmes, managing dependencies, risks and delivery transparency.
- Solution design & implementation: Lead the end-to-end delivery of AI-enabled systems, including agents, retrieval systems and supporting services. Ensure solutions align with enterprise architecture standards, responsible-AI requirements and operational readiness practices. Establish strong engineering ways-of-working across the squad, including review practices, reliability patterns and observability.
- Product mindset & continuous improvement: Shape product thinking around applied AI solutions, helping teams translate opportunities into scalable solution designs. Mentor engineers and develop high-potential talent across the capability. Contribute to thought leadership and help represent EY’s Applied AI Engineering capability in market-facing initiatives.
What we’re looking for
Essential skills & experience:
- Expert software and systems engineering: Python/TypeScript, distributed systems, API/microservice architecture and cloud‑native patterns.
- Deep applied AI/ML mastery: NLP/CV/transformers, generative models (GANs/VAEs), reinforcement learning, classical ML and statistical modelling.
- Advanced LLM/RAG engineering: prompt pipelines, embeddings, vector stores (FAISS/Milvus/Pinecone), hybrid retrieval, grounding, hallucination mitigation and evaluation frameworks.
- LLMOps/MLOps: automated testing, drift monitoring, safety/guardrails, CI/CD for ML, telemetry, lineage and governance.
- Cloud architecture leadership: Azure (preferred), AWS/GCP; Kubernetes/Docker; serverless; IAM, VNETs, zero‑trust patterns and secure network architecture.
- Data engineering architecture: Spark/Databricks, ETL/ELT frameworks; big‑data/graph stacks (Hadoop, Cassandra, Neo4j); streaming (Event Hub/Kafka).
- Enterprise integration: legacy/LOB systems, event workflows, case management platforms; design for high availability, resilience and observability.
- Product leadership: conducting discovery, framing hypotheses, shaping MVPs, backlog ownership, value/adoption metrics and client‑ready PRDs.
- Responsible AI & compliance: privacy‑by‑design, auditability, fairness and transparency; strong awareness of UK financial‑services regulatory context (FCA, PRA, GDPR).
- Consulting leadership: stakeholder management, commercial awareness, proposal shaping, solution positioning and creation of thought leadership.
- Demonstrated ability to lead multi‑disciplinary squads (engineering, data science, architecture, product, design) through complex delivery cycles.
Nice to have:
- Optional: governance/model‑risk/responsible‑AI certifications.
Technical Certifications (preferred):
- Azure AI Engineer (AI‑102) or Azure Data Scientist Associate.
- AWS Machine Learning Specialty or Google Professional ML Engineer.
- Databricks Machine Learning Engineer, Kubernetes (CKA/CKAD).
- Azure/AWS Solutions Architect certifications.
- Optional: governance/model‑risk/responsible‑AI certifications.
How you work
You’re hands-on when needed, but primarily you create the conditions for repeatable delivery: clear direction, strong ways-of-working, and high engineering standards. You earn trust with senior stakeholders by explaining trade-offs simply and steering delivery through ambiguity with strong governance and transparency.
What we offer
High-impact work with leading organisations across sectors, within a collaborative engineering-led AI capability. You will benefit from:
- Continuous development through the Applied AI Engineering Academy, where you both advance your expertise in scalable AI system design and contribute to the evolution of engineering standards, reusable accelerators and capability development across the team.
- Opportunities to participate in innovation challenges, internal accelerators and capability showcases.
- Learning and certification support across cloud, AI and engineering platforms.
- Competitive compensation and benefits.
- Flexible hybrid working arrangements depending on client needs.
Travel & Working Model
Hybrid working and periodic travel to client sites across the UK (and occasionally internationally), discussed based on projects and location.
Inclusion and accessibility
EY is committed to building an inclusive culture where everyone can thrive. If you require adjustments or support during the recruitment process, we encourage you to let us know.
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
Applied AI Engineering Squad Lead - Product & Engineering, Senior Manager, TC in London employer: FP&A
Contact Detail:
FP&A Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Engineering Squad Lead - Product & Engineering, Senior Manager, TC in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and engineering space. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and engineering. This is your chance to demonstrate your expertise in Python, cloud architecture, and all that good stuff. Make it easy for potential employers to see what you can do!
✨Tip Number 3
Prepare for interviews by diving deep into EY's values and recent projects. Understand their approach to responsible AI and how they’re shaping the future of engineering-led AI. Tailor your responses to show how you can contribute to their mission of building a better working world.
✨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. So, get clicking and let’s make it happen!
We think you need these skills to ace Applied AI Engineering Squad Lead - Product & Engineering, Senior Manager, TC in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Applied AI Engineering Squad Lead role. Highlight your experience with AI systems, engineering practices, and any relevant projects that showcase your skills in Python, TypeScript, or cloud architecture.
Showcase Your Leadership Skills: As a senior manager, we want to see how you've led teams in the past. Share examples of how you've guided squads through complex projects, managed client relationships, and driven successful outcomes in AI engineering.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experiences and achievements. Avoid jargon unless it's relevant to the role, and make sure your passion for AI and engineering shines through!
Apply Through Our Website: We encourage you to submit your application directly through our website. This way, you can ensure your application reaches the right people and stands out in our system. Plus, it’s super easy to do!
How to prepare for a job interview at FP&A
✨Know Your AI Stuff
Make sure you brush up on your knowledge of applied AI and engineering principles. Be ready to discuss specific technologies like Python, TypeScript, and cloud-native patterns. Show them you’re not just familiar with the concepts but can also apply them in real-world scenarios.
✨Showcase Your Leadership Skills
As a Squad Lead, you'll need to demonstrate your ability to lead multi-disciplinary teams. Prepare examples of how you've successfully guided teams through complex projects, managed stakeholder expectations, and ensured delivery transparency. They want to see your leadership style in action!
✨Understand Their Vision
Familiarise yourself with EY's mission and their focus on responsible AI. Be prepared to discuss how you can contribute to building AI systems that are secure, scalable, and aligned with enterprise standards. Showing that you understand their goals will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the role, team dynamics, and the future of AI at EY. This shows your genuine interest in the position and helps you gauge if the company culture aligns with your values. Plus, it’s a great way to engage with your interviewers!