Prompt/Generative AI Engineer at Aksigorta

Posted on (10 months ago)

Umraniye, Istanbul, Turkey
Hybrid

Industry: Insurance

Job Type: Full-time

Experience Level: Mid-Senior Level

Job Description

Aksigorta is formed by the synergy of Sabancı Holding who brings Turkey and the world together with its 16 companies in 9 sectors, and Ageas Group, a 150-year old global player of insurance industry. We have more than 60 years of experience as one of the biggest insurance companies in Turkey.

Responsibilities

  • Design and develop high-quality prompts and templates that guide the behavior and responses of large language models.
  • Work with our business and product professionals to understand the business use cases to which GPT and other large language models could be applied to.
  • Fine tune prompts to extract specific information or control the model's output, ensuring desired accuracy, relevance, and language fluency.
  • Optimize prompts to improve user interactions and system performance.
  • Test and evaluate the performance of prompts to ensure that they are producing the desired results.
  • Communicate effectively and contribute to a collaborative work environment.
  • Stay up-to-date on the latest research and trends in prompt engineering & LLMs, and incorporate these advancements into product.

Requirements

  • Bachelor's degree in computer science, engineering, artificial intelligence or a related field.
  • Experience in working with Large Language Models (LLMs) with a focus on prompt engineering or conversational AI.
  • Experience with deploying LLM models in production environments and working with software engineering teams.
  • Familiarity with prompt engineering techniques and methodologies, including designing and optimizing prompts to control model behavior and outputs.
  • Programming skills in languages such as Python.
  • Strong collaboration and communication skills to work effectively in Agile teams and present findings to stakeholders.
  • Strong problem-solving skills, with the ability to formulate solutions for complex language understanding and generation tasks.