At a Glance
- Tasks: Join a dynamic team to build AI-powered solutions for major organisations.
- Company: EY, a leader in engineering-led AI and innovation.
- Benefits: Competitive salary, flexible hybrid work, and learning opportunities.
- Other info: Collaborative environment with excellent career growth and diverse teams.
- Why this job: Make a real impact by transforming AI ideas into operational solutions.
- Qualifications: Basic software engineering skills and a passion for AI technologies.
The predicted salary is between 50000 - 70000 ÂŁ per year.
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.
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 sit at the intersection of software engineering, product thinking, and client delivery, working within a squad to build real AI‑powered solutions. You will collaborate with engineers, designers and client teams to turn complex problems into reliable systems. In this consultant role within the Forward Deployed Engineering team, you will develop foundational AI engineering and product skills within a delivery squad. You will learn how to design, build and integrate LLM/RAG features, contribute to discovery and user stories, and follow EY standards for quality, security and documentation while supporting demos and adoption.
What You’ll Do:
- Client‑facing engineering & delivery: Support discovery workshops by capturing requirements and helping translate them into user stories and acceptance criteria. Support demos, show‑and‑tells and feedback cycles; prioritise fixes and enhancements with the squad. Work effectively in diverse, multidisciplinary teams and produce client‑ready artefacts to agreed timelines.
- Solution design & implementation: Build LLM/RAG features and integrations under guidance, contributing clean, tested, maintainable code. Follow EY reference architectures, security patterns and evaluation baselines, contributing to documentation and reusable accelerators.
- Product mindset & continuous improvement: Contribute to documentation and reusable components/accelerators that help teams deliver consistently. Learn field lessons (what works in client environments) and feed that back through the squad’s delivery routines and artefacts.
What We’re Looking For:
- Essential skills & experience: Software engineering fundamentals (algorithms, data structures, APIs, microservice basics). Programming in Python and/or TypeScript; exposure to async patterns, testing, and version control (Git). LLM/RAG basics: embeddings, prompt design, retrieval patterns; willingness to learn evaluation and guardrails. Intro experience with data wrangling for structured and unstructured data; feature engineering fundamentals. Cloud fundamentals (Azure preferred); containers (Docker) and CI/CD exposure. Understanding of responsible‑AI principles, privacy and basic model‑risk concepts; eagerness to learn UK regulatory context (FCA, PRA, GDPR). Clear written and verbal communication; ability to operate in client environments and collaborate with security, risk and architecture teams. Growth mindset: curiosity, continuous learning, and ability to adapt quickly to new techniques and tools.
- Nice to have: Familiarity with ML concepts (regression, classification, clustering) and deep‑learning frameworks (PyTorch/TensorFlow). Foundational knowledge of data platforms (Spark/Databricks) and event/streaming patterns (e.g., Event Hub/Kafka). Technical Certifications (preferred) Microsoft Azure AI Engineer Associate (AI‑102) — in progress or planned. Azure Data Scientist Associate — in progress or planned. AWS Machine Learning Specialty or Google Professional ML Engineer — welcome. Databricks and Kubernetes (CKA/CKAD) — welcome for future development.
How You Work:
- You’re comfortable being hands‑on: coding, debugging, deploying, and iterating with users.
- You care about quality—but you’re pragmatic about what’s “good enough” to ship and improve safely, and you’re eager to learn from feedback.
- You can communicate clearly with both technical and non‑technical stakeholders as you build confidence in client settings.
What We Offer:
- High‑impact work with leading organisations across sectors, within a collaborative engineering‑led AI team.
You Will Benefit From:
- A structured FDE Academy and cohort learning experience.
- Opportunities to participate in hackathons, innovation challenges and engineering showcases.
- Learning and certification support across cloud and AI technologies.
- 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.
Consultant, AI Engineer TC FS 1 in London employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Consultant, AI Engineer TC FS 1 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 Consultant, AI Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for those interviews! Brush up on your software engineering fundamentals and be ready to discuss your experience with Python, TypeScript, and AI concepts. Practice common interview questions and think of examples that showcase your skills.
✨Tip Number 3
Show your passion for AI! During interviews, share your thoughts on the latest trends in AI and how you see it impacting businesses. This will demonstrate your enthusiasm and understanding of the field, making you stand out as a candidate.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive opportunities listed there that you won’t find anywhere else.
We think you need these skills to ace Consultant, AI Engineer TC FS 1 in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Consultant, AI Engineer role. Highlight your relevant skills in software engineering and AI, and show us how your experience aligns with what we're looking for.
Showcase Your Projects: If you've worked on any cool projects related to AI or software engineering, don’t hold back! Share them in your application. We love seeing practical examples of your work and how you tackle real-world problems.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon where possible. We want to understand your skills and experiences without having to decode complex terms!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our team at EY!
How to prepare for a job interview at hackajob
✨Know Your Tech Inside Out
Make sure you brush up on your software engineering fundamentals, especially algorithms, data structures, and APIs. Be ready to discuss your experience with Python or TypeScript, and don’t forget to mention any exposure to async patterns and version control with Git.
✨Show Off Your Problem-Solving Skills
Prepare to talk about how you've tackled complex problems in the past. Think of examples where you’ve built LLM/RAG features or contributed to user stories. This will demonstrate your ability to translate client needs into actionable solutions.
✨Communicate Like a Pro
Since this role involves client-facing work, practice explaining technical concepts in simple terms. You’ll need to show that you can collaborate effectively with both technical and non-technical stakeholders, so clear communication is key.
✨Embrace Continuous Learning
EY values a growth mindset, so be prepared to discuss how you stay updated with new technologies and techniques. Mention any relevant certifications you’re pursuing or have completed, especially in AI and cloud technologies, to show your commitment to professional development.