How do you make our customers happy?

By helping bol deliver a high-quality, scalable customer experience without increasing operational overhead. With millions of products and constant change, traditional processes can’t keep up. As an Engineer on the AI Efficiency Team, you’ll design and build AI Agents that streamline and optimise operational workflows. The result: customers find the right products faster, trust what they read, and enjoy a consistently great experience.

The biggest challenge

AI agents can’t solve a broken process; they’ll just highlight those flaws with ruthless efficiency. Most of bol’s workflows grew organically, human-centric, exception-heavy, and rarely standardized. They span multiple systems, and rely on human judgment at various points. You can’t just wrap an API around them and call it done. The challenge is to deeply understand these workflows: map them, decompose them, and evolve them into end-to-end automated and supported pipelines that sit between existing business processes and the current systems landscape.
You’ll build an automation and orchestration layer that integrates with existing operational excellence (OpEx) tooling owned by other teams. That means you need to understand both the business process above you and the technical systems below you. You’ll collaborate closely with business teams to understand and improve processes, and with OpEx teams to embed your solutions into their existing platforms.

You'll need to balance:
- Automation vs. trust — AI systems must be safe, traceable, and human-in-the-loop where it matters.
- Speed vs. integration quality — solutions must plug into existing systems cleanly, not create shadow infrastructure.
- Reusability vs. domain specificity — build modular capabilities that work across categories, not one-off scripts.
- Moving fast vs. building foundations — ship value now while laying the groundwork for scale.

What you will do as AI Automation Engineer

You’ll design, build, and operate agentic systems that automate operational workflows across bol. You’ll work in a cross-functional team alongside a Product Manager, data scientists, and domain stakeholders — turning messy manual processes into scalable, measurable, and trustworthy automated pipelines.

Your responsibilities include:

• Map and decompose workflows: Analyse existing operational processes and translate them into automatable components. Think like a business analyst and build like an engineer. You’ll understanding the “why” behind each step before designing the “how.”
• Build the automation and orchestration layer: Design and implement agent pipelines that sit between business processes and the existing systems landscape. Build triage agents, content generation agents, validation agents, and monitoring agents. Ensure these integrate cleanly with existing OpEx tooling via REST APIs, BigQuery, PubSub, and other integration patterns.
• Build with LLMs (but only where applicable and responsibly): Use large language models as core building blocks, but only where applicable. Design effective prompts, evaluations, and guardrails. Implement human-in-the-loop checkpoints where needed. Build traceability so every agent action can be explained and audited.
• Integrate, don’t isolate: Your solutions must plug into the existing systems landscape. Work with OpEx teams to ensure your automation layer integrates with their platforms. Existing OpEx ownership stays with the owning teams — your job is to orchestrate, not replace.
• Instrument and evaluate: Build feedback loops and evaluation frameworks. Define and track metrics like automation rates, throughput, error rates, and quality scores. Make the system observable so the team can iterate with confidence.
• Shape the team and its practices: This team is new. You’ll help define ways of working, technical standards, and engineering culture. You’ll contribute to hiring and set the bar for what good looks like.

Why you can make a difference

You bring:

- 5+ years of software engineering experience, comfort working in Python and Java/Kotlin backends and React frontends when needed.
- Experience with automation and orchestration — building pipelines, workflows, or agent systems that coordinate multiple steps and services.
- Practical experience with LLMs — prompt engineering, evaluation, chaining, tool use, and an understanding of capabilities and limitations.
- Strong system integration skills — REST APIs, BigQuery, PubSub, event-driven architectures, and working across system boundaries.
- Business analysis and process mapping aptitude — you can sit with an operational team, understand their workflow end-to-end, and translate it into a technical design.
- An outcome mindset — you care about whether the automation actually works, not just whether the code compiles.
- Comfort with ambiguity — this team is building something new, and you’ll help figure out what “good” looks like.
- Bonus: domain knowledge in e-commerce operations.

Where you'll be working

You’ll join the AI Efficiency team within bol’s Product & Tech organization, a newly formed group starting with a broad mandate and a blank slate. The environment is ambitious and collaborative: engineers, data scientists, and operational partners who all want AI to work flawlessly in production, not just in pitch decks. The team is still taking shape, which means you help define not only what we build, but how we work. If you’ve been waiting for a role where AI, product, and operational reality all meet – this is your opportunity.