At a Glance
- Tasks: Lead a squad in building AI-enabled solutions and drive delivery across complex programmes.
- Company: Join EY, a global leader in engineering-led AI innovation.
- Benefits: Competitive salary, flexible hybrid working, continuous development, and learning support.
- Other info: Dynamic environment with opportunities for career growth and innovation challenges.
- Why this job: Shape the future of AI while working with top organisations and diverse teams.
- Qualifications: Expertise in software engineering, AI/ML, and strong leadership skills required.
The predicted salary is between 60000 - 80000 £ per year.
Location: London (UK – Hybrid working with client‑site travel as required)
Salary: Competitive
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. As a Forward Deployed Engineer‑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 FDE 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. Through collaborative engineering challenges, knowledge sharing and capability initiatives, you will play an active role in strengthening how AI 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 FDE 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.
Senior Manager, Forward Deployed Engineer - Squad Lead, TC, FS in London employer: 慨正橡扯
At EY, we pride ourselves on being a leading employer that fosters a culture of innovation and collaboration, particularly in the rapidly evolving field of AI. Our commitment to continuous development through initiatives like the FDE Academy ensures that you will have ample opportunities for professional growth while working on high-impact projects with diverse teams. With flexible hybrid working arrangements and a focus on inclusivity, EY is dedicated to creating an environment where every employee can thrive and contribute to building a better working world.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Manager, Forward Deployed Engineer - Squad Lead, TC, FS in London
✨Tip Number 1
Network like a pro! Reach out to your connections on LinkedIn or at industry events. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for interviews by researching the company and its culture. We want to show that we’re not just a good fit for the role, but also for the team. Tailor your answers to reflect how your skills align with their goals.
✨Tip Number 3
Practice makes perfect! Do mock interviews with friends or use online platforms. We need to be confident in our responses and articulate our experiences clearly to impress those interviewers.
✨Tip Number 4
Don’t forget to follow up after interviews! A simple thank-you email can go a long way. It shows our enthusiasm for the position and keeps us fresh in their minds as they make their decision.
We think you need these skills to ace Senior Manager, Forward Deployed Engineer - Squad Lead, TC, FS in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior Manager, Forward Deployed Engineer role. Highlight your experience with AI systems and engineering leadership, as this will show us you’re a perfect fit for the squad.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that align with the job description, especially around AI, cloud architecture, and team leadership. We want to see how you’ve made an impact!
Be Clear and Concise:Keep your application clear and to the point. Use bullet points where possible and avoid jargon unless it’s relevant. We appreciate straightforward communication, so make it easy for us to see your qualifications.
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’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at 慨正橡扯
✨Know Your Tech Inside Out
Make sure you’re well-versed in the essential skills listed in the job description, like Python, distributed systems, and cloud architecture. Brush up on your knowledge of AI/ML concepts, especially those related to NLP and generative models, as these will likely come up during technical discussions.
✨Showcase Your Leadership Skills
As a Squad Lead, you'll need to demonstrate your ability to lead multi-disciplinary teams. Prepare examples from your past experiences where you successfully guided teams through complex projects, managed stakeholder expectations, and drove delivery outcomes.
✨Understand the Business Context
Familiarise yourself with EY’s focus on responsible AI and how it applies to the financial services sector. Be ready to discuss how you can help clients operationalise AI capabilities while ensuring compliance with regulations like GDPR and FCA standards.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current AI initiatives, team dynamics, or how they measure success in AI projects. This not only demonstrates your enthusiasm but also helps you gauge if the company is the right fit for you.
