Lead Engineer

Join our dynamic team as a Senior Developer, specializing in the implementation and prompt engineering of Large Language Models (LLMs). In this role, you will harness the power of state-of-the-art LLMs to revolutionize personalized communication and automated processes within a digitally-driven retail telecom environment. This position requires a strong technical foundation (70%) complemented by strategic business insights and prowess to write, validate and predict consumer prompts (30%), aimed at deploying scalable, high-impact LLM solutions that enhance digital commerce and customer interaction. The deep understanding of consumer interaction patterns in search, chatbot, etc is a must have.

Key Responsibilities:

• LLM Integration: Implement and refine large language models to develop cutting-edge systems for personalized customer interactions and automation, ensuring scalability and efficiency.
• Engineering Excellence: Employ advanced prompt engineering techniques to fine-tune LLM interactions, achieving tailored and contextually appropriate responses that elevate the consumer experience in the telecom retail sector.
• Optimization: Adapt and optimize open-source LLMs from platforms like Hugging Face, aligning them with specific consumer needs and seamlessly integrating them into our existing infrastructure.
• Innovation: Work closely with the digital marketing and customer experience teams to leverage LLMs in enhancing digital engagement, customer satisfaction, and e-commerce initiatives.
• LLM Management: Oversee the deployment, maintenance, and scaling of LLM solutions, prioritizing reliability, performance, and security across all digital platforms.

Required Skills and Experience:

• LLM Expertise: Strong proficiency in the implementation, integration, and management of large language models, with a deep understanding of their capabilities and potential applications.
• Proficiency: Advanced skills in programming and scripting, particularly in Python, essential for LLM development and customization.
• Architecture Acumen: Familiarity with cloud computing services and architectures, crucial for deploying and managing scalable LLM applications.
• Communication: Ability to articulate complex technical details and LLM strategies effectively to both technical and non-technical stakeholders.
• Qualifications:
• and E-commerce Experience: Background in the retail telecom sector, with insights into digital marketing, e-commerce challenges, and customer engagement strategies.
• Expertise: Experience with Google’s and OpenAI’s LLM ecosystems, applying these technologies to drive tangible improvements in customer experience and business operations.
• Leadership: Demonstrated success in leading cross-functional projects that integrate LLM technology to boost customer service and enhance operational efficiency.
• Portfolio: A robust portfolio of projects where LLM implementations have significantly improved customer engagement or streamlined operational processes.