Staff Deployment Engineer

Doghouse Recruitment; Amsterdam; On-site; EUR 113,000 - 138,000; Full time

Benefits offered by this job

Competitive pay

Equity possible

Flexible time off

Parental leave

Job summary

Doghouse Recruitment is seeking a Staff AI Deployment Engineer to join our Amsterdam team. You will split time between hands-on AI engineering and delivering solutions to customers, ensuring real business value from deployments.

You will collaborate across product, data science, cloud and platform teams, including US-based colleagues, and own customer projects from discovery to adoption in a highly autonomous role.

Qualifications

• Several years of AI Engineering or technical deployment experience, with 5+ years in customer-facing delivery.
• Strong Python programming skills.
• Experience with REST APIs, databases and Databricks.
• Ability to troubleshoot and explain technical concepts to stakeholders.

Responsibilities

• Lead end-to-end customer implementations, from technical discovery and integration to deployment and adoption.
• Design, build and deploy agentic AI workflows and automation solutions.
• Develop integrations using Python, REST APIs, databases and cloud-based technologies.
• Leverage AI-assisted coding tools such as Claude Code, Codex or Cursor to accelerate development.
• Troubleshoot technical issues, debug code and support production environments.
• Act as the main technical point of contact for customers, translating business requirements into practical solutions.
• Drive customer adoption, answer technical questions and ensure successful implementation.
• Collaborate with engineering, product and cloud/platform teams to resolve technical challenges.
• Independently identify priorities, take ownership of customer projects and guide more junior engineers.
• Contribute to global engineering operations, including on-call support.

Skills

Python programming

REST APIs

Databases

Databricks

Cloud architecture

AI engineering

Troubleshooting

Communication

Customer delivery

Tools

AWS

Azure

Docker

Kubernetes

Job description

We're partnering with a fast-growing, international technology company developing an AI-powered platform that helps enterprises and governments navigate complex global supply chains and international trade.

As part of their international expansion, they're looking for a Staff AI Deployment Engineer to join their team in Amsterdam.

In this role, you'll combine hands-on AI engineering with customer-facing technical delivery, spending approximately 50% of your time working directly with customers and 50% building, integrating and deploying technical solutions.

You'll be part of an international engineering and implementation team, working closely with product, data science, cloud and platform engineers, including daily collaboration with US-based colleagues.

This is a highly autonomous role where you'll take ownership of customer implementations, solve complex technical challenges and ensure AI solutions deliver real business value.

Responsibilities

• Lead end-to-end customer implementations, from technical discovery and integration to deployment and adoption.
• Design, build and deploy agentic AI workflows and automation solutions.
• Develop integrations using Python, REST APIs, databases and cloud-based technologies.
• Leverage AI-assisted coding tools such as Claude Code, Codex or Cursor to accelerate development.
• Troubleshoot technical issues, debug code and support production environments.
• Act as the main technical point of contact for customers, translating business requirements into practical solutions.
• Drive customer adoption, answer technical questions and ensure successful implementation.
• Collaborate with engineering, product and cloud/platform teams to resolve technical challenges.
• Independently identify priorities, take ownership of customer projects and guide more junior engineers.
• Contribute to global engineering operations, including on-call support.

Who Are We Looking For?

• Several years of relevant experience in AI Engineering, Solutions Engineering, Forward Deployed Engineering or technical implementation, ideally including 5+ years of customer-facing technical delivery.
• Strong hands-on Python programming skills.
• Solid understanding of data structures, SQL, databases and/or platforms such as Databricks.
• Practical experience building or deploying AI solutions, preferably involving LLMs or agentic AI.
• Comfortable working with AI-assisted coding tools such as Claude Code, Codex or similar.
• Experience with REST APIs, integrations and cloud architecture.
• Ability to independently troubleshoot, debug and solve technical problems.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders and vice versa.
• A customer-oriented mindset and genuine interest in combining engineering with customer interaction.
• Highly autonomous, proactive and comfortable taking ownership without constant direction.
• Comfortable working with international teams, particularly US-based colleagues.
• Willingness to travel to customer locations and participate in an on-call rotation.

Nice to Have’s

• Background in Solutions Engineering, Forward Deployed Engineering or Applied AI.
• Experience with Databricks, Spark or large-scale data processing.
• Familiarity with agentic AI frameworks such as LangChain, MCP or RAG.
• Experience with AWS, Azure, Docker or Kubernetes.
• Experience implementing enterprise software solutions.
• Knowledge of global trade, supply chains or logistics.
• Experience mentoring or guiding other engineers.

Benefits & Package

• Competitive compensation package - up to EUR125K;
• Potential equity participation and bonus or variable compensation.
• Flexible time-off policy.
• Paid parental leave.
• Opportunity to work with cutting-edge AI technology and international enterprise customers.
• High degree of autonomy, ownership and technical influence.
• Opportunity to play a key role in a growing international team.

Location & Travel:

Based in Amsterdam, with international collaboration and customer-site travel - you would need to sync with different time zones (US and Asia). Travel may reach approximately 50% during the initial months, with a lower frequency expected thereafter.