**DevOps Engineer | Surveillance**
Design, deploy, and manage secure cloud infrastructure using Terraform and Ansible. Implement CI/CD pipelines with Jenkins and GitLab. Monitor system health with Prometheus and Grafana. Troubleshoot issues and ensure high availability. Requires 5+ years' experience in DevOps, strong Linux expertise, and security clearance.
Point72, L.P. and its affiliates and our third-party partners use cookies and similar technologies to view and retain your site interactions to perform analytics, enable site functionality and assist our marketing efforts exclusively for recruiting purposes. By continuing to use our site, you consent to these data practices, as described in our Privacy Policy.
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. 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
About Point72
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
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A Career with Point72’s Surveillance Team
\n
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
\n
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
\n
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
\n
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
\n
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
About Point72
\n
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
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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.\u003C/p\u003E\u003Cbr\u003E\u003Ch3\u003EWhat you’ll do\u003C/h3\u003E\\n\u003Cul\u003E\u003Cli\u003ELead the design and build of scalable data infrastructure and pipelines to power surveillance analytics, enabling rapid exploration and production deployment of signals and models\u003C/li\u003E\u003Cli\u003EBuild and operate infrastructure as code to provision, secure, and manage cloud resources and platform services with an emphasis on repeatability and automation\u003C/li\u003E\u003Cli\u003EDesign and maintain containerized platforms and orchestration layers to run analytics and machine learning workloads reliably and efficiently at scale\u003C/li\u003E\u003Cli\u003EDevelop and maintain CI/CD pipelines and ML lifecycle automation to accelerate model development, validation, deployment, and rollback\u003C/li\u003E\u003Cli\u003EImplement and evolve observability, logging, and alerting across the stack to shorten time to detection and resolution for production incidents\u003C/li\u003E\u003Cli\u003EAutomate security controls, access management, and compliance checks within platform tooling to support regulated surveillance workflows\u003C/li\u003E\u003Cli\u003ECollaborate closely with data scientists, analysts, and security teams to translate surveillance requirements into production-ready, maintainable systems\u003C/li\u003E\u003Cli\u003EOptimize cloud cost, performance, and operational practices for large-scale data processing, storage, and model training workloads\u003C/li\u003E\u003Cli\u003EMentor engineers and contribute to platform best practices, documentation, and runbooks to drive continuous improvement and team impact\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWhat’s required\u003C/h3\u003E\\n\u003Cul\u003E\u003Cli\u003EBachelor\'s degree in computer science, engineering, or a related technical field, or equivalent professional experience\u003C/li\u003E\u003Cli\u003E5+ years of hands-on experience in cloud infrastructure, DevOps, or platform engineering supporting production data or machine learning workloads\u003C/li\u003E\u003Cli\u003EProven, hands-on experience with data warehouses and lakehouses such as Snowflake, Redshift, BigQuery, or Databricks\u003C/li\u003E\u003Cli\u003EStrong command of Infrastructure as Code with Terraform and Terraform Enterprise\u003C/li\u003E\u003Cli\u003EProficiency in containerization with Docker or Podman, orchestration using Kubernetes, AWS EKS, or ECS Fargate, and implementation of GitOps principles and workflows\u003C/li\u003E\u003Cli\u003EHands-on experience building CI/CD pipelines using GitHub Actions and automating model lifecycle using MLflow, Kubeflow, or Weights & Biases\u003C/li\u003E\u003Cli\u003EExperience operating observability and monitoring stacks including Datadog, AWS CloudWatch, and the Grafana ecosystem (Grafana, Loki, Prometheus)\u003C/li\u003E\u003Cli\u003EExtensive 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\u003C/li\u003E\u003Cli\u003EStrong scripting and programming skills in Python and Bash and proven experience operating Linux-based production systems\u003C/li\u003E\u003Cli\u003EAbility to work onsite in Stamford, CT and to communicate and troubleshoot effectively across cross-functional, distributed teams\u003C/li\u003E\u003Cli\u003ECommitment to the highest ethical standards\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWe take care of our people\u003C/h3\u003E\\n\u003Cp\u003EWe invest in our people, their careers, their health, and their well-being. 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**DevOps Engineer | Surveillance**
Design, deploy, and manage secure cloud infrastructure using Terraform and Ansible. Implement CI/CD pipelines with Jenkins and GitLab. Monitor system health with Prometheus and Grafana. Troubleshoot issues and ensure high availability. Requires 5+ years' experience in DevOps, strong Linux expertise, and security clearance.
Point72, L.P. and its affiliates and our third-party partners use cookies and similar technologies to view and retain your site interactions to perform analytics, enable site functionality and assist our marketing efforts exclusively for recruiting purposes. By continuing to use our site, you consent to these data practices, as described in our Privacy Policy.
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. 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
About Point72
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
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A Career with Point72’s Surveillance Team
\n
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
\n
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
\n
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
\n
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
\n
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
About Point72
\n
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
\n ","title":"DevOps Engineer, Surveillance","@type":"JobPosting","@context":"http://schema.org/"} CSJobDetailModule.init('{\"lastModifiedDateFormatted\":\"2026-08-19\",\"job\":{\"attributes\":{\"type\":\"Job__c\",\"url\":\"/services/data/v67.0/sobjects/Job__c/a03Vo00001dzWf7IAE\"},\"Id\":\"a03Vo00001dzWf7IAE\",\"Name\":\"DevOps Engineer, Surveillance\",\"Assigned_Internal_Recruiter__c\":\"005Vo00000XyPLsIAN\",\"Job_Code__c\":\"IVS-0014866\",\"Experience__c\":\"Experienced Professionals\",\"Company__c\":\"001j000000VbgAOAAZ\",\"Posted_Location__c\":\"Stamford\",\"Area__c\":\"Technology & Engineering\",\"Team__c\":\"Software & System Engineering\",\"Job_Description_External__c\":\"\u003Ch3\u003EA Career with Point72’s Surveillance Team\u003C/h3\u003E\\n\u003Cp\u003EPoint72’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.\u003C/p\u003E\u003Cbr\u003E\u003Ch3\u003EWhat you’ll do\u003C/h3\u003E\\n\u003Cul\u003E\u003Cli\u003ELead the design and build of scalable data infrastructure and pipelines to power surveillance analytics, enabling rapid exploration and production deployment of signals and models\u003C/li\u003E\u003Cli\u003EBuild and operate infrastructure as code to provision, secure, and manage cloud resources and platform services with an emphasis on repeatability and automation\u003C/li\u003E\u003Cli\u003EDesign and maintain containerized platforms and orchestration layers to run analytics and machine learning workloads reliably and efficiently at scale\u003C/li\u003E\u003Cli\u003EDevelop and maintain CI/CD pipelines and ML lifecycle automation to accelerate model development, validation, deployment, and rollback\u003C/li\u003E\u003Cli\u003EImplement and evolve observability, logging, and alerting across the stack to shorten time to detection and resolution for production incidents\u003C/li\u003E\u003Cli\u003EAutomate security controls, access management, and compliance checks within platform tooling to support regulated surveillance workflows\u003C/li\u003E\u003Cli\u003ECollaborate closely with data scientists, analysts, and security teams to translate surveillance requirements into production-ready, maintainable systems\u003C/li\u003E\u003Cli\u003EOptimize cloud cost, performance, and operational practices for large-scale data processing, storage, and model training workloads\u003C/li\u003E\u003Cli\u003EMentor engineers and contribute to platform best practices, documentation, and runbooks to drive continuous improvement and team impact\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWhat’s required\u003C/h3\u003E\\n\u003Cul\u003E\u003Cli\u003EBachelor\'s degree in computer science, engineering, or a related technical field, or equivalent professional experience\u003C/li\u003E\u003Cli\u003E5+ years of hands-on experience in cloud infrastructure, DevOps, or platform engineering supporting production data or machine learning workloads\u003C/li\u003E\u003Cli\u003EProven, hands-on experience with data warehouses and lakehouses such as Snowflake, Redshift, BigQuery, or Databricks\u003C/li\u003E\u003Cli\u003EStrong command of Infrastructure as Code with Terraform and Terraform Enterprise\u003C/li\u003E\u003Cli\u003EProficiency in containerization with Docker or Podman, orchestration using Kubernetes, AWS EKS, or ECS Fargate, and implementation of GitOps principles and workflows\u003C/li\u003E\u003Cli\u003EHands-on experience building CI/CD pipelines using GitHub Actions and automating model lifecycle using MLflow, Kubeflow, or Weights & Biases\u003C/li\u003E\u003Cli\u003EExperience operating observability and monitoring stacks including Datadog, AWS CloudWatch, and the Grafana ecosystem (Grafana, Loki, Prometheus)\u003C/li\u003E\u003Cli\u003EExtensive 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\u003C/li\u003E\u003Cli\u003EStrong scripting and programming skills in Python and Bash and proven experience operating Linux-based production systems\u003C/li\u003E\u003Cli\u003EAbility to work onsite in Stamford, CT and to communicate and troubleshoot effectively across cross-functional, distributed teams\u003C/li\u003E\u003Cli\u003ECommitment to the highest ethical standards\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EWe take care of our people\u003C/h3\u003E\\n\u003Cp\u003EWe invest in our people, their careers, their health, and their well-being. When you work here, we provide:\u003C/p\u003E\\n\u003Cul\u003E\u003Cli\u003EFully-paid health care benefits\u003C/li\u003E\u003Cli\u003EGenerous parental and family leave policies\u003C/li\u003E\u003Cli\u003EMental and physical wellness programs\u003C/li\u003E\u003Cli\u003EVolunteer opportunities\u003C/li\u003E\u003Cli\u003ENon-profit matching gift program\u003C/li\u003E\u003Cli\u003ESupport for employee-led affinity groups representing women, minorities and the LGBT+ community\u003C/li\u003E\u003Cli\u003ETuition assistance\u003C/li\u003E\u003Cli\u003EA 401(k) savings program with an employer match and more\u003C/li\u003E\u003C/ul\u003E\u003Cbr\u003E\u003Ch3\u003EAbout Point72\u003C/h3\u003E\\n\u003Cp\u003EPoint72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit \u003Ca href=\\\"https://www.Point72.com/working-here\\\\\\\" target=\\\"_blank\\\"\u003Ewww.Point72.com/working-here\u003C/a\u003E\u003C/p\u003E\u003Cbr\u003E\u003Ch3\u003E\u003C/h3\u003E\\n\u003Cbr\u003E\",\"Japanese_Job_Description_External__c\":\"\u003Cbr\u003E\u003Cbr\u003E\u003Cbr\u003E\",\"Transcript_Optional__c\":false,\"RecordTypeId\":\"012j0000000tcfoAAA\",\"Apply_Now_URL__c\":\"https://boards.greenhouse.io/point72/jobs/8531774002?gh_jid=8531774002\",\"Type__c\":\"Full Time\",\"LastModifiedDate\":\"2026-08-19T12:29:12.000+0000\",\"Location__c\":\"Stamford, Connecticut\",\"Company__r\":{\"attributes\":{\"type\":\"Account\",\"url\":\"/services/data/v67.0/sobjects/Account/001j000000VbgAOAAZ\"},\"Business__c\":\"Point72\",\"Name\":\"Point72 Asset Management, L.P.\",\"Id\":\"001j000000VbgAOAAZ\",\"RecordTypeId\":\"012j0000000tIlgAAE\"},\"RecordType\":{\"attributes\":{\"type\":\"RecordType\",\"url\":\"/services/data/v67.0/sobjects/RecordType/012j0000000tcfoAAA\"},\"DeveloperName\":\"Investment_Services\",\"Name\":\"Investment Services\",\"Id\":\"012j0000000tcfoAAA\"}},\"friendlyJobName\":\"devops-engineer-surveillance\",\"formattedTeam\":\"Software & System Engineering\",\"formattedLocation\":\"Stamford\",\"formattedArea\":\"Technology & Engineering\"}');