Devops Engineer, Surveillance A Career with Point72's Surveillance Team Point72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers.

The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.

WHAT YOU'LL DO

Lead the design and build of scalable data infrastructure and pipelines to power surveillance analytics, enabling rapid exploration and production deployment of signals and models Build and operate infrastructure as code to provision, secure, and manage cloud resources and platform services with an emphasis on repeatability and automation Design and maintain containerized platforms and orchestration layers to run analytics and machine learning workloads reliably and efficiently at scale Develop and maintain CI/CD pipelines and ML lifecycle automation to accelerate model development, validation, deployment, and rollback Implement and evolve observability, logging, and alerting across the stack to shorten time to detection and resolution for production incidents Automate security controls, access management, and compliance checks within platform tooling to support regulated surveillance workflows Collaborate closely with data scientists, analysts, and security teams to translate surveillance

Requirements

into production-ready, maintainable systems Optimize cloud cost, performance, and operational practices for large-scale data processing, storage, and model training workloads Mentor engineers and contribute to platform best practices, documentation, and runbooks to drive continuous improvement and team impact WHAT'S REQUIRED Bachelor's degree in computer science, engineering, or a related technical field, or equivalent professional experience 5+ years of hands-on experience in cloud infrastructure, DevOps, or platform engineering supporting production data or machine learning workloads Proven, hands-on experience with data warehouses and lakehouses such as Snowflake, Redshift, BigQuery, or Databricks Strong command of Infrastructure as Code with Terraform and Terraform Enterprise Proficiency in containerization with Docker or Podman, orchestration using Kubernetes, AWS EKS, or ECS Fargate, and implementation of GitOps principles and workflows Hands-on experience building CI/CD pipelines using GitHub Actions and automating model lifecycle using MLflow, Kubeflow, or Weights & Biases Experience operating observability and monitoring stacks including Datadog, AWS CloudWatch, and the Grafana ecosystem (Grafana, Loki, Prometheus) Extensive experience with AWS core services, including S3, EC2, Lambda, RDS, and EMR, and practical experience using Boto3 and AWS machine learning services such as SageMaker and Bedrock Strong scripting and programming skills in Python and Bash and proven experience operating Linux-based production systems Ability to work onsite in Stamford, CT and to communicate and troubleshoot effectively across cross-functional, distributed teams Commitment to the highest ethical standards WE TAKE CARE OF OUR PEOPLE We invest in our people, their careers, their health, and their well-being.

Benefits

Generous parental and family leave policies Volunteer opportunities Support for employee-led affinity groups representing women, people of color and the LGBT+ community Mental and physical wellness programs Tuition assistance