Time since we first saw it
Day 164
Up longer than most. Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
Head / Manager of Data & AI
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Permanent — employment source
Employment type in the employer’s posting: Permanent employee
From the employer’s posting
What you’ll work on
Full postingBuild and deploy LLM-based apps and AI agents (RAG, tool-calling)
Develop internal copilots and automation pipelines
Replace manual workflows and automate reporting, QA and operations tasks
Maintain and optimize the data warehouse and SQL pipelines
Define technical standards and track ROI of AI initiatives
From the employer’s posting
Build and deploy LLM-based applications and AI agents (RAG, tool-calling, multi-step workflows).
Develop internal copilots and automation pipelines.
Replace manual workflows with AI-driven solutions. Automate reporting, QA, and operational tasks.
Maintain and optimize the data warehouse (BigQuery/Snowflake). Manage SQL pipelines and ensure data quality.
Define standards and track ROI (time saved, efficiency, cost impact).
About Rovo
Rovo Group is one of Europe’s fastest-growing apparel production platforms, combining
In the employer’s words · Read in context
Posting record
Report an errorOpen 5 monthsWe first saw this posting 164 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026164 days ago
- Recorded sightings
- 85
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Rovo is hiring
1 open job
- No new data jobs since June
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- BigQuery
- dbt
- Looker
- Snowflake
Where the posting names them
Nice-to-Have - Proficiency in Python for AI and automation. - Experience with vector databases and semantic search.
- Maintain and optimize the data warehouse (BigQuery/Snowflake). - Manage SQL pipelines and ensure data quality. 4. Business Partnering & Execution
- Tool-calling / agent frameworks (LangChain or similar) - Strong SQL expertise and experience with modern data warehouses. - Experience integrating APIs and automating workflows.
3. Data Infrastructure & Quality - Maintain and optimize the data warehouse (BigQuery/Snowflake). - Manage SQL pipelines and ensure data quality.
- Experience with vector databases and semantic search. - Experience with dbt, Looker, or BI tools. - Background in high-growth or operationally complex environments.
Your next step
Complete your application on rovo-portugal-unipessoal-lda.jobs.personio.de. The employer’s form will show what is required.
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Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
Job Summary
Role Overview
Key Responsibilities
Preferred Qualifications (Must-have/Nice-to-have)
Benefits & Working Conditions
Application Process
About Rovo Group
Rovo Group is one of Europe’s fastest-growing apparel production platforms, combining
premium sourcing expertise with a next-generation digital stack. We operate three business units:
Rovo - Full-cycle development & manufacturing for fashion brands
Assembly - Custom merchandise with a seamless digital creation process
Index - Direct-to-consumer essentials with superior materials and fit
You’ll partner across all three, with a strong focus on Assembly’s digital platform and Rovo’s production workflows.
Role Overview
As Manager of Data & AI, you will lead and actively build Rovo’s AI and data capabilities. This is a hands-on role focused on designing, prototyping, and deploying AI systems, intelligent agents, and automation workflows that drive measurable business impact.
You will own the execution of AI initiatives across the company while ensuring a reliable, scalable data foundation. You are expected to spend a significant portion of your time building, not just managing.
Your mission is to turn AI into a practical execution layer that increases speed, reduces manual work, and enhances decision quality across Product, Operations, Finance, Sales, and Supply Chain.
Depending on the candidate’s experience, the role may be positioned at Manager or Head level.
Key Responsibilities
1. AI Systems & Agents
Build and deploy LLM-based applications and AI agents (RAG, tool-calling, multi-step workflows).
Develop internal copilots and automation pipelines.
Ensure reliability, monitoring, and guardrails.
2. Workflow Automation & Process Optimization
Replace manual workflows with AI-driven solutions.
Automate reporting, QA, and operational tasks.
Scale successful automations across teams.
3. Data Infrastructure & Quality
Maintain and optimize the data warehouse (BigQuery/Snowflake).
Manage SQL pipelines and ensure data quality.
4. Business Partnering & Execution
Turn business needs into practical AI solutions.
Prioritize high-impact initiatives and deliver measurable outcomes.
5. Measurement & Impact
Define technical standards and best practices.
Define standards and track ROI (time saved, efficiency, cost impact).
Preferred Qualifications (Must-have/Nice-to-have)
Must-Have
6 - 10 years in data, AI, analytics, or engineering roles.
Proven hands-on experience building AI-powered workflows or LLM applications.
Strong experience with:
LLM APIs (OpenAI, Anthropic)
Prompt engineering and structured outputs
RAG systems
Tool-calling / agent frameworks (LangChain or similar)
Strong SQL expertise and experience with modern data warehouses.
Experience integrating APIs and automating workflows.
Strong problem-solving and execution mindset.
Fluent in English.
Nice-to-Have
Proficiency in Python for AI and automation.
Experience with vector databases and semantic search.
Experience with dbt, Looker, or BI tools.
Background in high-growth or operationally complex environments.
Experience designing evaluation frameworks for LLM systems.
Benefits & Working Conditions
- Health insurance coverage.
- Flexible work schedules that promote work-life balance.
- Generous allocation of 26 vacation days per year.
- Collaborative and supportive work environment.
- Opportunity for professional growth and development.
- Modern and well-equipped office space in a convenient location.
Application Process
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Porto
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.