Description review
Senior Cloud Platform Engineer
Curotec · Remote · back to the listing
HR standards
50/100
needs work
Title ↔ description
49/100
poor
Reads as
Unclear
no confident match
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
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What the listing never says
- 18 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
The person would be working at the intersection of cloud infrastructure and AI/LLM engineering — specifically:
• Designing and deploying AI agents using Google’s Gemini models
• Using GCP’s Vertex AI as the primary ML platform (model hosting, pipelines, endpoints)
• Building with Google’s agent tooling — the Agent Development Kit (ADK) for constructing agent logic, and the Managed Agents API for running/orchestrating them at scale
• Likely involved in things like tool-calling, multi-agent orchestration, RAG pipelines, and connecting agents to enterprise systems
• Role Responsibilities
•
Architecting and implementing infrastructure as code (IaC).
• Defining administrative choices for environments that are auto-configured by IaC.
• Focus on agent use cases, including relationships with BigQuery databases, enterprise connectors, and agent orchestration.
• Heavy leverage of Vertex.
• Investigating and tweaking designs to avoid issues with Pfizer’s enterprise infrastructure and GCP limitations.
Requirements
• Required Skills and Experience
•
Strong background in GCP and Vertex.
• Experience with IaC technologies like Kubernetes, Terraform, and CI/CD.
• Enterprise environment experience is crucial to navigate existing GCP and ISRM teams and strictures.
•
Preferred transferable skills (due to rarity of specific Google ADK experience):
• Mature experience in AWS or Azure.
• Experience with Bedrock or Azure Agent Foundry.
• GCP experience combined with LangGraph or LangChain.
Originally posted on Himalayas
• Designing and deploying AI agents using Google’s Gemini models
• Using GCP’s Vertex AI as the primary ML platform (model hosting, pipelines, endpoints)
• Building with Google’s agent tooling — the Agent Development Kit (ADK) for constructing agent logic, and the Managed Agents API for running/orchestrating them at scale
• Likely involved in things like tool-calling, multi-agent orchestration, RAG pipelines, and connecting agents to enterprise systems
• Role Responsibilities
•
Architecting and implementing infrastructure as code (IaC).
• Defining administrative choices for environments that are auto-configured by IaC.
• Focus on agent use cases, including relationships with BigQuery databases, enterprise connectors, and agent orchestration.
• Heavy leverage of Vertex.
• Investigating and tweaking designs to avoid issues with Pfizer’s enterprise infrastructure and GCP limitations.
Requirements
• Required Skills and Experience
•
Strong background in GCP and Vertex.
• Experience with IaC technologies like Kubernetes, Terraform, and CI/CD.
• Enterprise environment experience is crucial to navigate existing GCP and ISRM teams and strictures.
•
Preferred transferable skills (due to rarity of specific Google ADK experience):
• Mature experience in AWS or Azure.
• Experience with Bedrock or Azure Agent Foundry.
• GCP experience combined with LangGraph or LangChain.
Originally posted on Himalayas