Engineering Manager - Data & AI (Hiring Immediately)

About Us 

As a leading group of companies, the ECA International Group stands as a global frontrunner in simplifying international mobility. Our collective vision is to make a positive impact by delivering exceptional products and services to our prestigious list of large enterprise clients. 

Our global presence across the UK, EU, Hong Kong, Australia, and the US offers our team a world of opportunities, and our commitment to innovation ensures that you will be at the leading edge of your field. 

We love to invest in our people’s success and development pathways, creating a diverse and inclusive community where your unique talents shine. Your work here has a global impact, and we prioritise work-life balance, offering flexibility to enable you to perform your best. Join us to experience a rewarding career where your potential is celebrated, and your journey to excellence begins. 

About the Job

This role is ideal for someone who wants to shape how a modern enterprise becomes truly AI-native. We already use AI in delivery and engineering, and we have strong guardrails and governance in place. Now, we’re looking for a leader who can help us scale: across data acquisition, ingestion, storage, and AI-powered consumption within a secure, multi-tenant environment.

You’ll evolve our existing data platform (AWS, Snowflake, S3, Postgres, event-driven services) into a product-facing, AI-ready foundation, while partnering across disciplines and leading a team in a supportive, high-trust environment.

If you're passionate about data, excited about AI, and motivated by meaningful impact, this role gives you the autonomy, influence, and visibility to shape how AI is adopted across the company.

Requirements

Key Responsibilities

1. Data platform evolution

• Take our current AWS/Snowflake/S3/Postgres setup and enable AI/RAG, product consumption, and multi-tenant access.
• Work with the Technical Architect to keep this aligned with our event-driven and security model.

2. Data acquisition & ingestion

• Design multi-source ingestion (APIs, scraping/crawling, file drops, crowdsourcing, agent-based pipelines).
• Make it observable, repeatable, and documented so research and analytics can plug in new sources without rework.

3. AI as a consumption layer

• Build LLM/RAG endpoints on top of our data and content as a service.
• Expose these services to Data Insights to enable users to ask, explore, and generate insights – not only download reports.

4. Partnering with Analytics

• Give the research teams clean, modelled, well-documented data.
• Turn one-off work into scheduled, production jobs.

5. Guardrails, governance, and quality

• Keep AI-generated code within SDLC, code review, and security bounds.
• Ensure data and AI services are audited and tenant aware.

6. Team leadership

• Lead a small technical team (data/AI/ingestion).
• Promote AI-native ways of working across product, data, and engineering.
• Manage and mentor your engineering team, fostering a collaborative, high-performance environment with excellent productivity.
• Demonstrate hands-on technical excellence while modelling accountability, critical thinking, and AI-first practices
• Set clear objectives, provide regular feedback, conduct performance reviews.

7. Delivery & Accountability

• Take full accountability for the delivery of high-quality software products, owning both successes and challenges
•  Drive outcome focused delivery planning and execution, measuring success by business impact rather than effort or hours invested
• Proactively identify and mitigate risks, making critical decisions to keep projects on track

8. Technical Direction & Architecture

• Guide technical direction, establish best practices, and ensure architectural decisions support scalability, maintainability, and business goals
• Be a hands-on contributor forArchitecting and building well-tested, maintainable applications
• Optimise tech stacks and development workflows to maximise team productivity

9. Agile & Product Collaboration

• Ensure Agile ceremonies (sprint planning, retrospectives, stand-ups) are followed and continuously refine Agile practices to optimise team performance 
• Collaborate with product owners and stakeholders to develop and maintain technical roadmaps that align with business strategy
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