About the role
<p>A Career with Point72's AI/ML – Investment Services Team</p> <p>The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning.</p> <p><strong>WHAT YOU'LL DO</strong></p> <ul> <li>Design and build scalable, high-performance backend systems that power investment services and AI-driven applications, and own their end-to-end lifecycle</li> <li>Build and operate robust data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers</li> <li>Integrate and productionize generative AI capabilities and large language model solutions, including model serving, embeddings, and API-based workflows to augment investment workflows</li> <li>Implement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security</li> <li>Optimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response</li> <li>Lead cross-functional delivery of prototypes into production by collaborating with data scientists, researchers, product owners, and operations teams</li> <li>Build and maintain CI/CD pipelines, automated testing, and deployment practices to accelerate safe delivery and rollback of services</li> <li>Mentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap</li> <li>Collaborate with security, compliance, and infrastructure partners to ensure data governance, access controls, and operational controls are integrated into solutions</li> </ul> <p><strong>WHAT'S REQUIRED</strong></p> <ul> <li>Bachelor's degree in computer science, software engineering, or a related technical field</li> <li>At least 5 years of professional software engineering experience with a focus on backend system engineering</li> <li>Experience building production data pipelines or data engineering solutions for batch and streaming data</li> <li>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</li> <li>Strong programming skills in one or more backend languages such as Java, Python, or Go, with demonstrated ability to design maintainable code and services</l