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Technology Artificial Intelligence Business ChatGPT Data Design GPT3 Information Technology

Navigating the Future with Generative AI: A Prompt Engineer Job Offer?

Looking through the lens of Generative AI, jobs are evolving rapidly in this age of Digital Augmentation. In the midst of all the artificial intelligence effervescence, I wonder what kind of new jobs will emerge soon.

One of them is the Prompt Engineer.

In this article, I imagined the job description of your business’ first Prompt Engineer.


YH SuperSleek Jeans fashion brand logo 01 1

The world is shifting rapidly. As a pioneer in generative AI and an advocate of productivity augmentation, we are excited to open the position of Prompt Engineer.

SuperSleek Jeans is a company providing tailored jeans to women and men. Our purpose is to make jeans like a second skin! Our values are sensorial audacity and durability leadership. We proudly employ 2700 talented souls dedicated to meeting people’s needs in a smart and compassionate manner. Technology plays a significant role in our way of working and exploring uncharted territories for the benefit of our employees and customers is part of our DNA.

We foster a dynamic and inclusive company culture that encourages growth, collaboration, and innovation. We offer competitive compensation packages, comprehensive benefits, and numerous opportunities for professional development.

Your Mission

Your mission is to establish and grow the practice of Prompt Engineering at SuperSleek Jeans.

Responsibilities

  1. Learn and teach how to build products faster by analyzing and modifying the chain of analysis-to-design, design-to-build, and build-to-supervise for augmentation in each domain.
  2. Lead the development of an Enterprise AI Spirit, a chat-based agent, sourcing its knowledge base from existing systems such as Wiki, Document Store, Databases, and Unstructured documents. Manage an up-to-date training data set.
  3. Build a corporate prompt catalog for workers to provide reusable productivity recipes.
  4. Determine which parts of business processes can be entirely automated.
  5. Establish KPIs, a Steering Dashboard, and periodic reporting to measure the benefits of AI-augmented engineering and operations compared to current systems of work.
  6. Introduce and evangelize the concept of Generative AI and Large Language Models (also known as LLM).
  7. Build a legal and ethical framework to ensure risks pertaining to AI augmentation are addressed accordingly. Monitor the progress of domestic and international AI regulations.

Your Skills

  1. Hands-on experience with Generative AI models and tools leveraging prompt engineering, such as ChatGPT, Midjourney, ElevenLabs, etc.
  2. Core background in IT engineering.
  3. Proven algorithmic skills and mastery of engineering practices.
  4. The ability to code in one of the most popular languages such as Python, JavaScript, Java, or C#. A basic understanding of SQL is a must.
  5. Data management proficiency.
  6. Excellent communication and ability to design stunning presentations with compelling storytelling.
  7. Critical thinking and root cause analysis capabilities.
  8. Conversational UX proficiency.

Soft Skills

  1. Autonomous leadership with the ability to identify and propose the next best actions for yourself and your colleagues.
  2. Effective change management and resistance handling.
  3. Leading by example and providing assistance to colleagues when needed.
  4. You walk the talk by advocating continuous augmentation and demonstrating how your productivity and quality increase with AI augmentation.

Benefits and Perks

  1. An 85k€ to 105k€ compensation package based on your experience in engineering and AI knowledge.
  2. Total health, dental, and vision insurance for all family members.
  3. Retirement savings plan according to the national compensation scheme.
  4. 30 holidays with a generous paid time off policy.
  5. Employee assistance program and wellness initiatives.
  6. Craft your own professional growth and development along with your manager
  7. Collaborative and inclusive company culture.
  8. Free cinema tickets for your team once per quarter.

Living Your First Days in our Company

  1. You start your onboarding as a treasure hunt which consists in visiting key people, visiting unusual places, and learning our way of working. Each step unlocks a new quest until the completion of your journey. Your manager, the employee experience manager officer, and teammates assist along your adventure.
  2. Receive training so that you can rapidly feel comfortable with internal tools.
  3. Enjoy a tour of the premises and surrounding environment, such as restaurants, shops, parks, etc.
  4. As you familiarize yourself with the work environment, your first responsibility will be establishing a plan for transitioning our organization from Digital Transformation to Digital Augmentation.

Join and become part of a team that shapes the future of SuperSleek Jeans. Apply now and embark on an exciting and fulfilling career journey with us.


Feel free to unapologetically copy and remix this potential job offer in your business transition to Digital Augmentation.

I might even use it in the future. Who knows!

🖖

Categories
Data Architecture Business Business Strategy Data Information Technology Legal Technology Strategy

The European Data Act: actually, can your data become a reliable source of income?

data economy 1

The European Data Act has recently been published.

It aims at clarifying and strengthening the governing framework of the #dataeconomy.

In the nutshell (extract):

“The Data Act will give both individuals and businesses more control over their data through a reinforced data portability right, copying or transferring data easily from across different services, where the data are generated through smart objects, machines, and devices.”

For example, a car or machinery owner could choose to share data generated by their use with its insurance company.

Such data, aggregated from multiple users, could also help to develop or improve other digital services, e.g. regarding traffic, or areas at high risk of accidents.”

Some thoughts on this

1️⃣ I wonder to what extent the boundaries of your data ownership can be explicitly defined, then transparently coded in IT systems, so that a “data asset” is legally bound to you as your property.

2️⃣ After this, you could ask Facebook, Instagram, and TikTok to share a piece of the cake: % of the revenue generated from your data.
Let’s face it, it looks like a game-changer, if it can really be implemented.

3️⃣ Ultimately, you can capitalize on GPDR architecture. It pushes the concepts of data ownership, consent management, data counters, data KPI, data censorship management, IAM, data expiry management, etc.

4️⃣ Beyond multicloud oversight solutions, this is an excellent use case for permissioned blockchain, like Hyperledger Fabric. (e.g. Infrachain )

5️⃣ Innovative business models to arise like “Mutual Data Funds”, or Open Data Lakes”, where a set of businesses or individuals would provide a set of qualified and certified data sources to act as “Value Added Data Sources”, something similar to Bloomberg or Reuters for financial News.

Also, these Mutual Data Pools are fitted to be plugged as Oracles in blockchains (#ethereum#chainlink#binance, etc.)

I can already envision the pitch of startups like “We are the Bloomberg of space mining Data” (which would be awesome by the way👍)

6️⃣ This could boost the API economy. But also push further the adoption of GraphQL and AsyncAPI standards.

7️⃣ I reckon open industry data models are a much better way to start. It would help regulators (e.g. Commission de Surveillance du Secteur Financier (CSSF) , CNPD – Commission nationale pour la protection des données , CNIL – Commission Nationale de l’Informatique et des Libertés), auditors and regtech (e.g. Scorechain ) to have a common ground to build their control frameworks and oversight infrastructure.
Now, it is time to stitch them together.

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Categories
Data Architecture Data Architecture Information Technology Master Data Management

Getting Started with Master Data Management (MDM)

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Image by Gerd Altmann

The MDM journey should definitely start with an analysis and the identification of the short-term goals you want to achieve. In fact, MDM will be a service for the whole company.

MDM is for:

  • A mall for your most valuable data
  • Contains end-to-end footprints of your business activities
  • An aggregation of rigorously organized data
  • Its scope starts with your core business information
  • Offers data-driven views of your processes that span over multiple lines of business.

You should start your MDM journey by:

  1. Analyze in detail the pros and cons of putting in place MDM. MDM is more about governance as distributed discipline than technology.
  2. Create a core project team that will analyze and defend the establishment of MDM in your company.
  3. Launch an awareness campaign. Then, educate people about the advantages and responsibilities when the business is operated with MDM
  4. Identify which data will be part of the MDM Strategy
  5. Define an Enterprise Data Model (EDM). This is a common catalog so that everybody in the company understands the business terms. Thus, it is also a means for calibrating internal communication. Ultimately, your MDM system is the digital implementation of your EDM
  6. Identify and standardize your Reference Data
  7. Design your Information System Architecture as to which data flows and systems will take part in it.
  8. Choose an MDM system technology. This application will be the core of the MDM execution and operations. Take into account the available skills on the market.
  9. Define your Data Quality Indicators because data quality management is paramount.
  10. Establish the MDM governance processes and roles (data owners and stewardship)
  11. Design your firsts reports and dashboards, then collect feedback about their value. As a result of this, increase the data scope by iteration.
  12. Communicate a LOT the benefits of MDM, to finally advertise the benefits. For instance, those would come from the golden data source, improved data quality, richer dashboards, unlocked analytics insights, etc.

Also, MDM is not a one-time exercise, it is a continuous practice. So make sure there is an organization owning the MDM system and the MDM governance!