At a Glance
- Tasks: Design and implement AI systems that make a real-world impact.
- Company: Join EY, a leader in engineering-led AI innovation.
- Benefits: Competitive pay, flexible hybrid work, and continuous learning opportunities.
- Other info: Collaborative environment with excellent career growth and hackathon opportunities.
- Why this job: Be part of a team shaping the future of AI in diverse sectors.
- Qualifications: Experience in software engineering, AI/ML, and cloud technologies.
The predicted salary is between 60000 - 80000 € per year.
About the job hackajob is collaborating with EY to connect them with exceptional professionals for this role. 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.
Location: UK (London CP / Manchester / Birmingham / Edinburgh/ Belfast) — Hybrid working with client-site travel as required. Contract: Permanent, full-time
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, you will contribute to the design and delivery of AI-enabled systems that operate reliably in enterprise environments. Working within a delivery squad, you will take ownership of defined engineering components and support the development of production-ready AI capabilities. You will work at the intersection of software engineering, product thinking and client delivery, helping translate complex problems into working solutions deployed in real-world environments. In this Senior Consultant role, you will operate as a hands-on engineer within a squad, designing and implementing AI capabilities such as agents, RAG pipelines and supporting services while ensuring solutions meet enterprise standards for reliability, security and governance.
What you'll do:
- Client-facing engineering & delivery: Collaborate with client stakeholders and internal teams to understand requirements and translate them into engineering tasks and deliverables. Contribute to workshops, demos and solution reviews while communicating technical considerations clearly to mixed audiences. Support the adoption of delivered solutions through testing, iteration and feedback cycles.
- Solution design & implementation: Design and implement AI-enabled components such as RAG pipelines, agents and supporting microservices. Integrate solutions with enterprise data sources, APIs and existing platforms while maintaining reliability and security standards. Apply responsible-AI guardrails, monitoring and operational practices to ensure safe and maintainable deployments.
- Product mindset & continuous improvement: Contribute to defining MVP scope, engineering tasks and delivery milestones within the squad. Implement evaluation approaches, monitoring and dashboards to understand system performance and user impact. Capture reusable engineering patterns and contribute to shared accelerators used across projects.
What we're looking for:
- Essential skills & experience: Software engineering: Python and/or TypeScript, async patterns, testing/CI, API design and microservice fundamentals. RAG engineering: retrieval strategies, chunking/indexing, hybrid search, grounding and hallucination mitigation. Applied AI/ML: hands-on with LLMs, embeddings and vector databases (FAISS/Milvus/Pinecone). LLMOps & evaluation: prompt pipelines, automated/offline evaluation, safety/guardrails, telemetry, versioning and CI/CD for ML. Cloud engineering: Azure (preferred) and/or AWS/GCP; Kubernetes/Docker; serverless (Azure Functions/Lambda); secure networking/IAM. Data engineering: Spark/Databricks, ETL/ELT pipelines; integration with client data sources and enterprise systems; runbooks and operational handover. Product delivery: workshop facilitation, PRDs, user stories and acceptance criteria; backlog ownership; roadmap and release planning. Measurement: define value/adoption metrics; implement simple dashboards or analysis to evidence impact and inform iteration. Responsible AI & compliance: privacy‑by‑design, model‑risk, auditability; awareness of UK expectations (FCA, PRA, GDPR). Consulting behaviours: client‑ready communication, time management and collaboration in diverse, multi‑disciplinary teams.
- Nice to have: Document & graph stores (e.g., Neo4j) and streaming patterns (Event Hub/Kafka). Azure/AWS Solutions Architect exposure; optional governance/model‑risk/responsible‑AI credentials.
Technical Certifications (preferred): Microsoft Azure AI Engineer Associate (AI‑102) or Azure Data Scientist Associate. AWS Machine Learning Specialty or Google Professional ML Engineer. Databricks (Data Engineer/ML Engineer) and Kubernetes (CKA/CKAD). Azure/AWS Solutions Architect; optional model‑risk/responsible‑AI governance credentials.
How you work: You’re comfortable being hands-on and shipping in short cycles while staying pragmatic about trade-offs. You can explain trade-offs simply and earn trust with clients and teammates; you operate well in ambiguity and prioritise quickly. You care about quality, operability and safe iteration (runbooks/observability/rollback).
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, strengthening the technical capabilities required to build and operate AI systems in production environments. Opportunities to participate in hackathons, engineering showcases and innovation challenges. 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 Consultant, AI Engineer in London employer: hackajob
At EY, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. With a strong focus on continuous development through the FDE Academy, competitive compensation, and flexible hybrid working arrangements, we provide exceptional opportunities for growth and innovation in the rapidly evolving field of AI engineering. Join us in London, Manchester, Birmingham, Edinburgh, or Belfast, and be part of a collaborative team dedicated to building a better working world.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Consultant, AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current or former EY employees on LinkedIn. Ask them about their experiences and any tips they might have for landing the Senior Consultant role. Personal connections can give you insights that job descriptions just can't.
✨Tip Number 2
Prepare for the interview by practising common questions related to AI engineering and consulting behaviours. We recommend doing mock interviews with friends or using online platforms. The more comfortable you are, the better you'll perform!
✨Tip Number 3
Showcase your skills through a portfolio! If you've worked on relevant projects, create a simple website or GitHub repository to display your work. This gives you a chance to demonstrate your expertise in Python, AI, and cloud engineering.
✨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 at EY. Plus, it shows you're serious about joining their team and contributing to building a better working world.
We think you need these skills to ace Senior Consultant, AI Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior Consultant role. Highlight your experience with AI engineering, Python, and any relevant projects that showcase your skills. We want to see how you fit into our vision!
Showcase Your Technical Skills:Don’t hold back on detailing your technical expertise! Mention your experience with LLMs, cloud platforms like Azure, and any certifications you have. This is your chance to shine and show us what you can bring to the table.
Communicate Clearly:When writing your application, keep it clear and concise. Use straightforward language to explain your experiences and how they relate to the role. Remember, we’re looking for someone who can communicate effectively with diverse teams!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets the attention it deserves. Plus, you’ll find all the details you need about the role and our company culture there!
How to prepare for a job interview at hackajob
✨Know Your Tech Inside Out
Make sure you’re well-versed in the essential skills listed in the job description, like Python, TypeScript, and AI/ML concepts. Brush up on your knowledge of RAG engineering and cloud platforms like Azure. Being able to discuss these topics confidently will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems using AI solutions. Think about how you can translate technical jargon into relatable terms for mixed audiences. This will demonstrate your ability to communicate effectively with clients and team members alike.
✨Emphasise Collaboration and Client Engagement
Since this role involves client-facing work, be ready to talk about your experience in collaborative environments. Share instances where you’ve facilitated workshops or contributed to solution reviews, highlighting your ability to engage stakeholders and drive projects forward.
✨Be Ready for Hands-On Challenges
Expect practical questions or scenarios during the interview that require you to think on your feet. Prepare to discuss how you would approach designing and implementing AI-enabled components. Showing that you can handle ambiguity and prioritise tasks will set you apart from other candidates.
