At a Glance
- Tasks: Lead AI engineering projects and guide teams in delivering scalable solutions.
- Company: Join a forward-thinking tech company focused on AI innovation.
- Benefits: Competitive salary, flexible hybrid work, and continuous learning opportunities.
- Other info: Engage in hackathons and innovation challenges for hands-on experience.
- Why this job: Make a real impact in AI while developing your skills in a collaborative environment.
- Qualifications: Experience in software engineering, AI/ML, and cloud architecture is essential.
The predicted salary is between 60000 - 80000 £ per year.
Location: London
Other locations: Primary Location Only
Salary: Competitive
Date: 9 Apr 2026
Job description Requisition ID: 1700054
Location: UK (London CP / Manchester / Birmingham / Edinburgh/ Belfast) — Hybrid working with client-site travel as required.
Contract: Permanent, full-time
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.
What you’ll do
- Client‑facing engineering & delivery: Lead technical delivery for AI solution areas, guiding teams in translating client needs into scalable engineering approaches. Engage with business and technology stakeholders to shape technical direction, communicate trade-offs and ensure alignment on solution outcomes. Support delivery teams in navigating complex client environments while ensuring engineering quality and reliability.
- Solution design & implementation: Architect AI‑enabled services such as agents, RAG pipelines and supporting platform components. Ensure solutions are designed with reliability, observability and operational readiness in mind. Guide teams in implementing responsible‑AI controls, evaluation approaches and engineering best practices.
- Product mindset & continuous improvement: Mentor engineers and support the development of strong engineering practices across squads. Lead technical reviews and help establish reusable patterns, accelerators and reference architectures. Contribute to internal knowledge sharing and external thought leadership around applied AI engineering.
What we’re looking for
Essential skills & experience:
- Software & systems engineering: Python/TypeScript, distributed systems, API/microservice design, testing/CI/CD.
- Applied AI/ML: building and operating ML/DL in production; expertise in NLP/CV/transformers and classical ML.
- LLM/RAG engineering: embeddings, vector stores (FAISS/Milvus/Pinecone), retrieval strategies, grounding and hallucination mitigation.
- LLMOps: prompt pipelines, automated evaluation, telemetry/drift monitoring, model versioning and release management.
- Cloud architecture: Azure (preferred) and/or AWS/GCP; Kubernetes/Docker; serverless; IAM and network security.
- Data engineering: Spark/Databricks, ETL/ELT; collaboration with platform/data teams to deliver cloud‑native data + AI architectures.
- Enterprise integration: legacy/LoB systems; design for reliability/observability (SLIs/SLOs) and operational readiness with runbooks/SRE practices.
- Product leadership: discovery facilitation, PRDs, acceptance criteria, prioritisation (RICE/MoSCoW), value/adoption metrics.
- Responsible AI & compliance: privacy‑by‑design, auditability and UK regulatory awareness (FCA, PRA, GDPR).
- Consulting capabilities: stakeholder management, client‑ready communication, time/budget/risk management and team leadership.
Nice to have:
- Big‑data/graph stacks (e.g., Hadoop, Cassandra, Neo4j) and streaming (Event Hub/Kafka).
- Azure/AWS Solutions Architect experience; 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 are hands‑on with engineering while setting the technical direction for delivery teams. You help teams navigate technical trade‑offs and ensure solutions meet enterprise standards for reliability and security. You care about quality, operational readiness and long‑term maintainability of systems delivered to clients.
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 architecture and engineering leadership capabilities required to build AI systems at scale.
- 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.
Manager, Forward Deployed Engineer, TC, FS employer: 慨正橡扯
As a forward-thinking employer in the heart of London, we offer a dynamic work environment that fosters innovation and collaboration. Our commitment to continuous development through the FDE Academy ensures that employees have ample opportunities for growth, while our flexible hybrid working model promotes a healthy work-life balance. Join us to engage in high-impact projects with leading organisations and be part of a culture that values inclusivity and accessibility.
StudySmarter Expert Advice🤫
We think this is how you could land Manager, Forward Deployed Engineer, TC, FS
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for those interviews! Research the company and its projects, especially in AI and engineering. Show them you’re not just another candidate but someone who’s genuinely interested in their work.
✨Tip Number 3
Practice your pitch! You want to be able to clearly explain how your skills in Python, cloud architecture, and AI can help them solve their challenges. Keep it concise and impactful.
✨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 take that extra step!
We think you need these skills to ace Manager, Forward Deployed Engineer, TC, FS
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Manager, Forward Deployed Engineer role. Highlight your experience with AI solutions and engineering practices that align with what we’re looking for.
Showcase Your Technical Skills:Don’t hold back on showcasing your technical expertise! Mention your experience with Python, cloud architecture, and any relevant certifications. We want to see how you can contribute to our engineering-led AI capability.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to see your key achievements and skills. We appreciate straightforward communication!
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!
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 technical skills listed in the job description, especially Python, TypeScript, and cloud architecture. Brush up on your knowledge of AI/ML concepts and be ready to discuss how you've applied them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've navigated complex client environments or tackled engineering challenges. Use the STAR method (Situation, Task, Action, Result) to structure your responses and highlight your impact.
✨Engage with Stakeholders
Demonstrate your consulting capabilities by discussing how you’ve managed stakeholder expectations in previous roles. Be ready to talk about how you communicate technical trade-offs and ensure alignment on solution outcomes.
✨Emphasise Continuous Improvement
Talk about your experience mentoring others and how you’ve contributed to establishing best practices within teams. Highlight any initiatives you've led that focused on improving engineering quality and operational readiness.
