DevOps Engineer, Surveillance

Point72; New York (NY); On-site; USD 160,000 - 250,000; Full time

Benefits offered by this job

Fully-paid health care benefits

Generous parental and family leave policies

Mental and physical wellness programs

Tuition assistance

401(k) savings program with employer match

Job summary

Point72 is looking for a dedicated professional to join their Surveillance team, focusing on developing and optimizing scalable data infrastructure to enhance analytics. The ideal candidate should have a Bachelor's degree in a technical field, extensive experience with cloud systems, and a commitment to high ethical standards. The role offers a competitive salary ranging from $160,000 to $250,000, alongside comprehensive benefits that aim to support employee well-being and professional development.

Qualifications

• 5+ years of hands-on experience in cloud infrastructure, DevOps, or platform engineering.
• Proven experience with data warehouses and lakehouses.
• Strong command of Infrastructure as Code with Terraform.
• Extensive experience with AWS services like S3, EC2, and Lambda.

Responsibilities

• Lead the design and build of scalable data infrastructure.
• Collaborate closely with data scientists and analysts.
• Automate security controls and compliance checks.
• Mentor engineers and contribute to documentation.

Skills

Cloud infrastructure

DevOps

Platform engineering

Infrastructure as Code with Terraform

Containerization with Docker or Podman

Kubernetes

CI/CD pipelines using GitHub Actions

Python and Bash scripting

Education

Bachelor's degree in computer science, engineering, or related technical field

Tools

AWS Core Services

Snowflake

Datadog

Grafana

Job description

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

Qualifications

• 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

Benefits

We invest in our people, their careers, their health, and their well‑being. When you work here, we provide:

• Fully‑paid health care benefits
• Generous parental and family leave policies
• Mental and physical wellness programs
• Volunteer opportunities
• Non‑profit matching gift program
• Support for employee‑led affinity groups representing women, minorities and the LGBT+ community
• Tuition assistance
• A 401(k) savings program with an employer match and more

The annual base salary range for this role is $160,000–$250,000 (USD), which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.