AI Engineer

Mission

Build and deploy a wide range of AI solutions end-to-end

forecasting algorithms, classification and regression models, LLM-powered tools, AI agents, or any technique best suited to the problem at hand.

Own the full lifecycle of every solution

• from design and implementation through production deployment, monitoring, and continuous improvement based on user feedback.
• Collaborate closely with the AI Platform team to
• leverage
• shared infrastructure, align on technical architecture, and get guidance on the AI stack.
• Communicate progress and findings clearly to both technical peers and non-technical stakeholders; present results to chapter leads and business owners.
• Produce lightweight documentation and run enablement sessions so business teams can work confidently alongside the solutions you create.

Build from the ground up

Join us at the beginning of this journey, working closely with the team

Lead

to shape the strategy, culture, and technical foundations of our new team.

You will be the bridge between business teams and AI solutions.

That means sitting with non-technical stakeholders, asking the right questions, mapping their workflows, and translating messy real-world problems into clear requirements before a single line of code is written. You're as much a translator and trusted partner to the business as you are an engineer.

Your profile

Journey to impact

Month 1

Get up to speed with 1–2 business units. Understand their data, workflows, and business context. Pick up the first strategic brief from the AI Strategist

Principal, and

deliver a working AI prototype that solves a real daily pain point.

Month 3

• Have at least one solution running in production. Incorporate feedback from real users,
• stabilise
• monitoring, and document the solution. Begin a second
• chapter
• engagement and broaden the range of AI techniques you apply.

Month 6

• Become a trusted enabler within the company and the Strategy team. Your solutions are running reliably and reusable components are being picked up by other teams.
• We're looking for someone at the intersection of AI engineering and business understanding, who can turn a department's problems into working AI solutions.

AI &

technical foundation

Strong Python skills and practical experience across the AI/ML spectrum: forecasting, classification, regression, LLMs, and agentic frameworks (

LangChain

,

LlamaIndex

,

CrewAI

, or equivalent). Comfortable owning solutions in production.

Familiarity with Docker/K8s or

MLOps

• tooling.
• Engineering fundamentals

Working knowledge of cloud platforms (AWS, GCP, or Azure)

, REST APIs (

FastAPI

• or similar), and SQL for data access and integration.
• Business & requirements acumen

• Able to sit with a non-technical team, ask the right questions,
• identify
• what
• actually matters
• , and translate messy real-world context into a clear implementation plan.
• Communication & collaboration

Clear and confident communicator with both technical and non-technical audiences. You can explain what a model does

,

• and what it
• can't
• do

,

to someone with no AI background.

Startup mindset & ownership

Comfortable with ambiguity, proactive, and accountable.

You

• have the ability to take a vision and bring it to life.
• We're looking for someone with
• hands-on experience building and shipping AI solutions
• in a professional setting. You'll feel at home taking ownership of your work from start to finish and making an impact within your first few weeks