Requirements

Bachelor's degree in computer science, software engineering, or a related technical field
At least 5 years of professional software engineering experience with a focus on backend system engineering
Experience building production data pipelines or data engineering solutions for batch and streaming data
Demonstrated experience developing or integrating generative AI and large language model solutions, such as model serving, embedding pipelines, fine-tuning workflows, or production integration with model APIs
Strong programming skills in one or more backend languages such as Java, Python, or Go, with demonstrated ability to design maintainable code and services
Experience deploying and operating services on cloud platforms and container platforms using Docker and container orchestration technologies
Proven experience building CI/CD pipelines, automated testing, and infrastructure-as-code for service deployments
Strong data skills including SQL, data modeling, and experience with both relational and non-relational data stores
Excellent verbal and written communication skills in English and demonstrated ability to collaborate with technical and non-technical stakeholders
Commitment to the highest ethical standards

What You'll Be Doing

Design and build scalable, high-performance backend systems that power investment services and AI-driven applications, and own their end-to-end lifecycle
Build and operate robust data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers
Integrate and productionize generative AI capabilities and large language model solutions, including model serving, embeddings, and API-based workflows to augment investment workflows
Implement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security
Optimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response
Lead cross-functional delivery of prototypes into production by collaborating with data scientists, researchers, product owners, and operations teams
Build and maintain CI/CD pipelines, automated testing, and deployment practices to accelerate safe delivery and rollback of services
Mentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap
Collaborate with security, compliance, and infrastructure partners to ensure data governance, access controls, and operational controls are integrated into solutions

Sports card
Private life insurance
Private medical and dental care, with vision allowance
Private pension scheme
Volunteer opportunities
Support for employee-led affinity groups representing women, people of color and the LGBT+ community
Business travel accident insurance
Employee assistance program
Educational assistance reimbursement