Senior Forward Deployed Engineer

About the role

This role within Business Enablement Engineering focuses on advancing how internal teams operate through AI and automation. The position targets complex operational challenges across finance, support, and legal workflows. Success is defined by faster, more reliable day-to-day execution for enterprise teams.

Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.

Key facts

What you'll do

Solutions for non-technical workflows are built and enhanced using existing internal tools and stakeholder platforms. Productivity across Legal, Support, and Operations is increased by reducing manual toil through tailored automation.

Long-term systems and runbooks are created and maintained to ensure stability and clear ownership. Documentation handover allows internal teams to manage solutions independently after project completion.

Patterns in stakeholder issues are analyzed and fed into the Business Enablement Tooling roadmap to guide future development.

End-to-end delivery of technical solutions is handled directly, from initial design through deployment and measurable business outcomes. Critical code is written, systems are configured, and issues are resolved to ensure impactful implementation.

Proofs-of-concept and minimum viable products are developed quickly using Adyen's launch-fast approach. Feedback from business users is gathered early and often to refine solutions.

Complex data integrations on GCP and Kubernetes, along with advanced AI agent orchestration, are analyzed and resolved throughout the project lifecycle.

Requirements

Expertise in software engineering enables independent building, troubleshooting, and scaling of scripts and automation tools. Hands-on experience with large language models, prompt engineering, and applied ML workflows is required.

Integration with third-party AI models such as Gemini is demonstrated using agentic orchestration frameworks including LangChain, LlamaIndex, and Google ADK. Google Cloud Platform skills, especially Vertex AI, are applied alongside on-premise infrastructure such as Kubernetes and Postgres.

Enterprise application rollouts and maintenance across Slack, Zoom, and the Atlassian suite have been successfully executed. Non-technical problems are translated into precise technical requirements with clarity and precision.

Stakeholder conversations are navigated confidently, with complex concepts explained through high-quality documentation and clear communication. Solutions are designed with a security-first mindset to protect data and user experience.

A hands-on, get-things-done mentality drives fast delivery and autonomous leadership of technical initiatives.

Practical notes

This position is based in the Amsterdam office and requires in-person presence. Remote-only arrangements are not available for this role. Travel expectations and team details align with standard company practices.

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

The role centers on financial technology, payments infrastructure, and data platforms used by global enterprises. AI, automation, and cloud-native tools are central to modern workflows in this field. Clear documentation, rapid prototyping, and measurable impact are emphasized in production environments. Collaboration across functions and strong communication skills are essential for success in this position.