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- Tasks: Lead the evolution of a data platform to support AI and multi-tenant access.
- Company: Modern, data-driven enterprise embracing AI with strong governance.
- Benefits: Influence AI adoption, strong executive support, and a high-trust culture.
- Why this job: Shape AI as a core capability and make a real impact.
- Qualifications: Experience with AWS, Snowflake, and a passion for AI technologies.
- Other info: Opportunity to mentor a team while remaining hands-on technically.
The predicted salary is between 48000 - 72000 ÂŁ per year.
Lead the Data Platform Behind an AI-Native Enterprise. I’m working with a modern, data-driven enterprise that is already using AI in delivery and engineering — with strong governance, security, and guardrails in place. Now they’re ready for the next step. This role is about scaling AI properly: across data acquisition, ingestion, storage, and AI-powered consumption, within a secure, multi-tenant environment. You’ll have the mandate — and the trust — to shape how AI becomes a first-class capability across the business.
The Opportunity
You’ll evolve an existing data platform (AWS, Snowflake, S3, Postgres, event-driven services) into a product-facing, AI-ready foundation. This isn’t a greenfield rebuild — it’s thoughtful evolution:
- Enabling AI / RAG and LLM-powered consumption
- Turning data into services, not just reports
- Making AI safe, observable, governed, and scalable
You’ll partner closely with architecture, analytics, product, and engineering — and lead a small, high-trust technical team.
What You’ll Be Doing
- Evolve the data platform to support AI, multi-tenant access, and product consumption
- Design robust ingestion pipelines (APIs, crawling/scraping, files, crowdsourcing, agent-based pipelines)
- Build AI as a consumption layer — LLM endpoints that let users explore and generate insights
- Enable analytics teams with clean, modelled, production-ready data
- Own governance and quality — auditability, tenancy, security
- Lead and mentor a small team, while remaining hands-on technically
- Drive delivery and accountability, measuring success by business impact
- Shape technical direction, architecture, and best practices
- Embed AI-native ways of working across product, data, and engineering
The Ideal Candidate
This role is ideal for someone who is:
- Data-first: You understand how data actually arrives in an organisation — APIs, files, partner feeds, human-sourced inputs, the internet — and the trade-offs around latency, quality, and governance.
- Technically comfortable with:
- AWS (core services, IAM, networking basics)
- Snowflake (or similar cloud data warehouse)
- Amazon S3 for landing and staging data
- Event-driven architectures for pipelines and services
Why This Role
- Real influence over how AI is adopted across the company
- Strong executive support and existing governance
- High trust, low ego culture
- A chance to turn AI from “experiments” into core capability
If this sounds like the kind of challenge you’re ready for — or you know someone who’d be a great fit — feel free to DM me directly.
Engineering Manager employer: FGS Recruitment
Contact Detail:
FGS Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Engineering Manager
✨Tip Number 1
Network like a pro! Reach out to people in your industry, especially those already working in AI and data platforms. A friendly chat can lead to insider info about job openings that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to data platforms and AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by diving deep into the company’s tech stack. Familiarise yourself with AWS, Snowflake, and event-driven architectures. Being able to discuss these technologies confidently will impress your interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Engineering Manager
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with data platforms and AI. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Show Your Passion for AI: We’re looking for someone who’s genuinely excited about AI and its potential. Share any personal projects or learning experiences related to AI/LLMs that demonstrate your enthusiasm and knowledge in your application.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experience and achievements. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at FGS Recruitment
✨Know Your Data Inside Out
Make sure you understand the data landscape of the company. Familiarise yourself with how data is acquired, ingested, and stored, especially in relation to AWS, Snowflake, and S3. Be ready to discuss your experience with these technologies and how they can be leveraged for AI.
✨Showcase Your AI Enthusiasm
Demonstrate your passion for AI and LLMs during the interview. Share examples of how you've implemented AI solutions in previous roles and how you envision AI becoming a core capability in the organisation. This will show that you're not just technically skilled but also genuinely excited about the potential of AI.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions. Brush up on your knowledge of event-driven architectures, ingestion pipelines, and governance practices. Be prepared to explain your thought process when designing robust systems and how you ensure data quality and security.
✨Emphasise Leadership and Collaboration
Since this role involves leading a team, be ready to talk about your leadership style and how you mentor others. Highlight your experience in collaborating with cross-functional teams, such as architecture and analytics, to drive successful outcomes. Show that you can balance being hands-on while also guiding a team.
