We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

We are seeking a software engineer with expertise in python and prior experience in utilizing LLMs. As an LLM Engineering Lead within Asset and Wealth Management you will be collaborating closely with various teams to prototype, build, test and deploy a large scale federated LLM platform. You will work with an agile team that will work on building, and delivering trusted market-leading technology products in a secure, stable, and scalable way. You will partner with our Global Data Science teams to design, develop, deploy and operate machine learning driven applications and data pipelines.

 

Job responsibilities

Hands on involvement in building and operating highly sophisticated LLM driven applications.Partnering directly with other technology teams on LLM projects to advise and assist as needed.Collaborating with engineering teams, product, to deliver state of the art LLM based solutions. Executing creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.Developing secure high-quality production code, and reviews and debugs code written by others.

 

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experienceEducated to degree level in a computer science or related discipline.Advanced python programming skills.Proven experience in building and operating scalable ML-driven products.Azure and/or AWS Certifications ( Architect, Big Data, AI/ML ) and hands on experience in Azure and AWSProficiency with cloud technologies like Kubernetes, Airflow.Experience working in a highly regulated environment.Proven ability to iterate quickly.Proficient in all aspects of the Software Development Life Cycle.Terraform, IaaC experience.Experience with design & delivery of large scale cloud-native architectures and microservices performance tuning, performance optimization, real-time applications.

 

Preferred qualifications, capabilities, and skills

Experience with financial data and data science.