At a Glance
- Tasks: Design and deliver AI-enabled systems for major organisations, translating complex problems into real-world solutions.
- Company: Join EY, a leader in engineering-led AI, shaping the future of enterprise technology.
- Benefits: Enjoy competitive pay, flexible hybrid work, continuous learning, and exciting project opportunities.
- Other info: Participate in hackathons and innovation challenges while growing your career in a supportive environment.
- Why this job: Be part of a dynamic team driving innovation and making a real impact with AI technology.
- Qualifications: Experience in software engineering, AI/ML, and strong collaboration skills are essential.
The predicted salary is between 60000 - 80000 £ 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.
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:
- 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.
- 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.
- 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.
- 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.
- Consulting behaviours: client‑ready communication, time management and collaboration in diverse, multi‑disciplinary teams.
- Document & graph stores (e.g., Neo4j) and streaming patterns (Event Hub/Kafka).
- 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.
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.
Forward Deployed AI Engineer — Senior Consultant (Hybrid UK) employer: hackajob
At EY, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As a Senior Consultant in Forward Deployed AI Engineering, you will engage in high-impact projects with leading organisations while benefiting from continuous development opportunities through the FDE Academy, flexible hybrid working arrangements, and a commitment to innovation. Join us in shaping a better working world, where your contributions are valued and your career can flourish.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed AI Engineer — Senior Consultant (Hybrid UK)
✨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 Forward Deployed AI Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for those interviews! Brush up on your Python and TypeScript skills, and be ready to discuss your experience with AI/ML projects. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with diverse teams.
✨Tip Number 3
Showcase your hands-on experience! Bring examples of your work with RAG pipelines, microservices, or any relevant projects to the table. This will help demonstrate your practical skills and how you can contribute to EY's engineering-led AI initiatives.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're serious about joining EY and being part of their mission to build a better working world.
We think you need these skills to ace Forward Deployed AI Engineer — Senior Consultant (Hybrid UK)
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Forward Deployed AI Engineer role. Highlight your experience with Python, TypeScript, and any relevant AI/ML projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Problem-Solving Skills:In your application, share examples of how you've tackled complex engineering challenges in the past. We love seeing candidates who can translate technical jargon into real-world solutions, so don’t hold back on those success stories!
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to describe your experiences and achievements. We appreciate a well-structured application that makes it easy for us to see your potential.
Apply Through Our Website:We encourage you to submit your application 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’re well-versed in the essential skills listed in the job description, especially Python, TypeScript, and AI/ML concepts. Brush up on RAG engineering and be ready to discuss your hands-on experience with LLMs and vector databases. This will show that you’re not just familiar with the tech but can also apply it effectively.
✨Prepare for Real-World Scenarios
Expect to tackle practical problems during the interview. Think about how you would design and implement AI-enabled components or integrate solutions with existing platforms. Practising these scenarios will help you articulate your thought process clearly and demonstrate your problem-solving skills.
✨Communicate Clearly and Confidently
Since you'll be collaborating with diverse teams and clients, practice explaining complex technical concepts in simple terms. Use examples from your past experiences to illustrate your points. This will not only showcase your expertise but also your ability to connect with non-technical stakeholders.
✨Show Your Passion for Continuous Learning
EY values continuous development, so be prepared to discuss how you keep your skills sharp. Mention any relevant certifications, courses, or projects you’ve undertaken recently. This demonstrates your commitment to growth and aligns with EY’s focus on building a better working world through innovation.
