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We are currently seeking an experienced professional to join our team in the role of Senior Full Stack Engineer.
Business: Emerging Technology, Innovation, and Ventures
Principal responsibilities
This role involves supporting the end-to-end delivery lifecycle, including software development, testing, and operational support, with a focus on generative AI. Key responsibilities include:
1. Taking ownership of products and services, developing technology solutions to meet customer needs, particularly in AI-driven contexts.
2. Responsible for LLM In-House Deployment, especially on private cloud.
3. Collaborating with engineers, architects, and stakeholders to drive AI-powered product/service direction.
4. Creating and automating high-quality code, testing pipelines, and technical test plans to ensure robustness and scalability in AI-based applications.
5. Working with DevOps teams to identify and address operational issues (e.g., performance, scalability) in AI systems.
6. Managing incidents related to AI/ML services, ensuring resilience and recovery objectives are met.
7. Automating CI/CD pipelines with a focus on AI model deployment and continuous improvement.
8. Staying updated on AI tools, technologies, and regulations, particularly around data privacy and generative AI.
Qualifications
1. Entrepreneurial mindset with an interest in AI, especially generative AI.
2. Advanced degree (MS/PhD preferred) from top institutions.
3. Familiar with LLM In-House Deployment.
4. Full stack engineering skills, with experience in AI frameworks (e.g., GPT, LLMs).
5. Contributions to AI communities or open-source projects preferred.
6. Knowledge of financial services (e.g., banking, insurance) is advantageous.
7. Ability to interpret academic research in AI and fintech.
8. Strong analytical, problem-solving, and communication skills in a fast-paced environment.
9. DevOps and agile experience, with adaptability to evolving AI responsibilities.
Functional/Technical Knowledge
1. Hands-on experience in solutions architecture and enterprise AI engineering.
2. Expertise in microservices, containerization, and scalable AI model deployment.
3. Familiarity with cloud platforms (AWS, GCP, Ali Cloud) and AI frameworks (e.g., TensorFlow, PyTorch).
4. Proficiency in programming languages (e.g., Python, Golang, Node.js) and database systems (relational and NoSQL).
5. Deep understanding of object-oriented programming and AI integration in complex systems.
6. Over 8 years of post-bachelor experience, with significant exposure to AI development and architecture.