Software Engineer - AI Integration at Oxford Economics in Dubai, United Arab Emirates

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Job Description

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 <p>
  We are seeking a skilled Software Engineer with expertise in Generative AI and Large Language Models (LLMs) to help grow adoption across our organisation. As part of our AI Platform team, you will play a pivotal role in developing and deploying systems that leverage the power of LLMs and generative AI. Your responsibilities will include interpreting AI use cases, building and integrating solutions, optimising performance, and ensuring seamless deployment. If you are passionate about AI, thrive in an agile environment, and have a knack for effective communication and stakeholder management, we&rsquo;d love to hear from you!
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 <p>
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  As our lead AI Engineer, you will work with the in-house team behind our first wave of AI Assistants and Tools in use across Oxford Economics. Your team will be part of an established team of customer-focused individuals who are passionate about solving complex problems at scale. Our databanks and modelling software provide clients across the world with advanced economic forecasting technology covering a range of industrial and commercial scenarios. Your team will own and maintain its own software and be responsible for ensuring the quality and information security of your deliverables.
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 </p>
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  <strong>
   Main Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    AI Integration
   </strong>
   : Collaborate with the product team to integrate AI features into our platform such as NLP, chatbot frameworks, and AI model APIs that enhance product value.
  </li>
  <li>
   <strong>
    Software System Development and Maintenance
   </strong>
   : Design, develop, and maintain software systems integral to LLMs and Generative AI. These systems form the backbone of your platform, directly contributing to its core functionality.
  </li>
  <li>
   <strong>
    Optimization and Efficiency
   </strong>
   : Optimize existing software for performance, scalability, and reliability. Improving current systems ensures efficiency, scalability, and user satisfaction.
  </li>
  <li>
   <strong>
    Security and Vulnerability Prevention
   </strong>
   : Implement robust security measures, including following our SDLC, conforming to ISO27001 and protecting against SQL injection attacks. Security is paramount to safeguard user data and prevent vulnerabilities.
  </li>
  <li>
   <strong>
    Communication
   </strong>
   : Implement APIs for seamless communication between our platform and key external services e.g. OpenAI.
  </li>
  <li>
   <strong>
    Data Privacy and Compliance
   </strong>
   : Work with our Head of Information Security to ensure data privacy and compliance with relevant regulations and that relevant legal and ethical considerations are incorporated to build trust.
  </li>
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   <strong>
    User Authentication and Access Control
   </strong>
   : Implement secure authentication mechanisms for user access. Define access controls and permissions for different user roles to ensure proper data handling and user management.
  </li>
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   <strong>
    User Insights and Experience
   </strong>
   : Ensure correct instrumentation and management of performance and usage data to allow integration of valuable usage data to help drive business strategy.
  </li>
  <li>
   <strong>
    System Stability and Performance
   </strong>
   : Conduct load testing to optimize performance. Monitor system performance proactively and address bottlenecks to maintain system health.
  </li>
  <li>
   <strong>
    Pricing Strategy and Collaboration
   </strong>
   : Work with senior business stakeholders and product owners to implement pricing models tied to usage that can drive adoption and successful product monetization.
  </li>
 </ul>
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 </p>
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  <strong>
   Key Working Relationships
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  <strong>
   Internal:
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 <ul>
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   Software Developers / Product Owner
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   Head of Information Security
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   Economists / Consulting Teams
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   External:
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   Cloud providers
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   Software vendors
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 </p>
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  <strong>
   Skills and Experience: Required
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   At least 4 years of software development experience across the product lifecycle in a modern engineering environment (APIs, CI/CD, Cloud infrastructure, Git, Agile, Scrum)
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  <li>
   Proficiency in programming languages: Python, Typescript and C#
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 </ul>
 <p>
  <br/>
 </p>
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  Commercial experience in the following:
 </p>
 <ul>
  <li>
   Writing production features leveraging LLMs and generative AI
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  <li>
   Adding vector search to production applications using vector databases
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  <li>
   Interacting with relational datasets with dynamic SQL
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   Cloud computing platforms - Azure, AWS, or GCP
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   Serverless architecture, azure function apps or similar (such as AWS lambda).
  </li>
 </ul>
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  <br/>
 </p>
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  Solid understanding of the following concepts:
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 <ul>
  <li>
   How embedding models work and how they are used for semantic search.
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   Information retrieval systems in general and how to use traditional IR tools and systems to monitor, measure, and optimize the results of our retrieval systems.
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   Prompt engineering in the context of production applications, knowing the capabilities and limitations of LLMs, and having a good intuition of where and when we should delegate functionality to them.
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   Strong Problem-Solving Skills and ability to identify critical issues and propose effective solutions.
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   Ability and collaborate effectively with cross-functional teams.
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   Understanding of microservices architectures and distributed systems
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   Understanding of data structures, algorithms, and software design principles
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   Experience building and maintaining large-scale software systems
  </li>
  <li>
   Knowledge of modern software engineering practices (CI/CD, containerization)
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  <li>
   Comfortable working independently and handling ambiguity
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Skills and Experience: Desired
  </strong>
 </p>
 <ul>
  <li>
   University honours degree qualification preferably in Computer Science, Mathematics, Statistics, or other quantitative fields, or related work experience
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  <li>
   Domain experience / demonstrable interest in economics-related fields
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   Experience or familiarity with AI model evaluation techniques
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   Understanding of the state of the art in generative AI, including RAG, LoRA, RLHF and others
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  <li>
   UI/UX: Ability to create intuitive user interfaces.
  </li>
  <li>
   Working understanding of Dev Ops, CI/CD and integrating systems into a deployment pipeline including cloud development (Azure preferred)
  </li>
  <li>
   An understanding of object-orientation, idiomatic and pattern-oriented, modern software design, programming principles and development best practices
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <em>
   Oxford Economics is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
  </em>
 </p>
 <p>
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 </p>
 <p>
  <strong>
   About Oxford Economics
  </strong>
 </p>
 <p>
  Oxford Economics was founded in 1981 as a commercial venture with Oxford University&rsquo;s business college to provide economic forecasting and modelling to UK companies and financial institutions expanding abroad. Since then, we have become one of the world&rsquo;s foremost independent global advisory firms, providing reports, forecasts and analytical tools on more than 200 countries, 250 industrial sectors, and 7,000 cities and regions. Our best-of-class global economic and industry models and analytical tools give us an unparalleled ability to forecast external market trends and assess their economic, social and business impact.
 </p>
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  <br/>
 </p>
 <p>
  Headquartered in Oxford, England, with regional centres in London, New York, and Singapore, Oxford Economics has offices across the globe in Belfast, Boston, Cape Town, Chicago, Dubai, Frankfurt, Hong Kong, Houston, Johannesburg, Los Angeles, Melbourne, Mexico City, Milan, Paris, Philadelphia, Sydney, Tokyo, and Toronto. We employ over 600 full-time staff, including more than 400 professional economists, industry experts and business editors&mdash;one of the largest teams of macroeconomists and thought leadership specialists. Our global team is highly skilled in a full range of research techniques and thought leadership capabilities, from econometric modelling, scenario framing, and economic impact analysis to market surveys, case studies, expert panels, and web analytics.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We look forward to welcoming you to the Oxford Economics family.
 </p>
</div>

AI Powered Job Insights

They are seeking a skilled Software Engineer specializing in AI Integration at Oxford Economics to enhance their organization with Generative AI and Large Language Models (LLMs). This position involves developing and deploying innovative systems while communicating effectively with various stakeholders.

📍 Location: Dubai, United Arab Emirates  
💼 Position: Software Engineer - AI Integration  
📅 Date Posted: 2024-04-16  

Role Summary:  
- Contribute to the development of AI Assistants and Tools  
- Collaborate within a customer-focused team  
- Ensure software quality and information security  

What You'll Do:  
- Integrate AI features into platforms using NLP and chatbot frameworks  
- Design, develop, and maintain systems for LLMs and Generative AI  
- Optimize software for performance, scalability, and reliability  
- Implement robust security measures and user authentication  
- Ensure compliance with data privacy regulations  
- Conduct load testing and monitor system performance  
- Collaborate on pricing strategy tied to product usage  

What's Needed:  
- 4+ years in software development, familiar with APIs, CI/CD, and Agile  
- Proficiency in Python, Typescript, and C#  
- Experience with LLMs and generative AI application  
- Knowledge of cloud platforms like Azure, AWS, or GCP  
- Strong understanding of data structures, algorithms, and software design principles  
- Ability to work independently and handle ambiguity  

Desired Skills:  
- University degree in Computer Science or related field  
- Interest in economics or related fields  
- Understanding of AI model evaluation techniques  
- Familiarity with UI/UX principles and modern DevOps practices  

This opportunity offers a chance to be part of a global advisory firm recognized for its analytical tools and economic forecasts, contributing to significant projects across various industries.

Top Interview Questions

  • Q: Can you explain your experience with integrating large language models (LLMs) into existing software applications? What challenges did you face and how did you address them?

    A: In my previous role, I integrated LLMs into our customer support chatbot system. The main challenge was ensuring that the annotated data for training was comprehensive enough to achieve high accuracy. I addressed this by conducting a thorough review of previous queries and implementing a feedback loop from users to continuously refine the model. Implementing A/B testing helped us compare different model performances and iteratively improve our service.

  • Q: Describe a situation where you had to optimize a software system for performance and scalability. What tools or methodologies did you use?

    A: I once worked on a data processing system that was struggling with large influxes of user data. I implemented a microservices architecture, which allowed us to scale individual components independently. We utilized containerization with Docker, along with Kubernetes for orchestration, ensuring our services could scale up during peak loads. Performance monitoring was done using Prometheus, which helped us identify bottlenecks effectively and optimize both the system and response times.

  • Q: How do you ensure data privacy and compliance with relevant regulations when building AI-integrated systems?

    A: I adhere to data protection standards such as GDPR by implementing data anonymization techniques and ensuring that any personal information is processed only when necessary. I work closely with our Head of Information Security to embed privacy protocols into our software development lifecycle (SDLC). Additionally, conducting regular audits and assessments helps ensure compliance with legal frameworks, maintaining user trust and system integrity.

  • Q: What strategies do you use to communicate technical information effectively to non-technical stakeholders?

    A: I believe in using analogies and simplifying technical jargon when explaining concepts to non-technical stakeholders. Visual aids like flowcharts or demos can provide clearer insights into complex systems. For instance, when discussing the workings of an AI feature, I might compare it to a human decision-making process to help them understand its relevance and application in business contexts. Regular check-ins with stakeholders also ensure that their concerns are understood and addressed.

  • Q: Can you elaborate on your experience with implementing security measures in software applications, particularly around SQL injection vulnerabilities?

    A: In a past project, I implemented several security best practices to prevent SQL injection attacks. This included using parameterized queries through ORM frameworks to ensure user input was safely handled, rather than directly embedding it into SQL statements. We also conducted regular security audits and employed vulnerability scanning tools to stay ahead of potential threats. Additionally, training the development team on security best practices helped cultivate a security-first mindset within the organization.

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