Full-Time

Security Comm Officer

Posted on 5/9/2026

Stanford Health Care

Stanford Health Care

10,001+ employees

Compensation Overview

$32.46 - $36.54/hr

Palo Alto, CA, USA

In Person

Category
Security & Protective Services
Requirements
  • High School Diploma or GED (General Educational Development) equivalent
  • Two years of progressively responsible and directly related work experience
  • CADL - California Drivers License - Valid And In State
  • PPSO - California Proprietary Private Security Officer License required within 90 Days or SGRC - Security Guard Registration Card required within 90 Days
  • Ability to adapt to and deal with change and ambiguity
  • Ability to generate ideas, consult with departments, and coordinate administrative solutions to alleviate security problems
  • Ability to observe and recall names, places and incidents, read and understand laws, ordinances, departmental rules and policies
  • Ability to plan, organize, prioritize, work independently and meet deadlines
  • Ability to relate to others in a calm, tactful and courteous manner
  • Ability to solve problems and identify solutions
  • Ability to speak and write effectively at a level appropriate for the job
  • Ability to work in a fast-paced work environment
  • Ability to work well with individuals at all levels of the organization
  • Knowledge of computer systems and software used in functional area
  • Knowledge of local, state and federal regulatory requirements related to areas of functional responsibility
  • Knowledge of police/law enforcement procedures and techniques
  • Physical requirements as needed to perform the job functions
Responsibilities
  • Answers all telephone calls promptly and courteously.
  • Triages calls rapidly, prioritizes and dispatches calls in appropriate order and importance.
  • Closely monitors radio traffic during any situation presenting potential danger to the life or safety of personnel and dispatches additional personnel as needed.
  • Maintains current status of personnel in the field.
  • Maintains radio contact with officer personnel and enforces proper radio control and courtesy.
  • Monitors CCTV system to identify suspicious people and circumstances and dispatches personnel as appropriate.
  • Monitors fire and other system alarms and makes appropriate notification of alarm activations.
  • Questions emergency callers to elicit complete and accurate information necessary for emergency response. Enters all appropriate information into the dispatch computer system. Maintains accurate records and logs reflecting the outcome and details of all calls and incidents.
  • Responds to requests made at the customer window at the security operations center. Responds to the medical center during activation of Disaster Plan.
  • Selects emergency response levels and personnel in accordance with established policies and procedures, as directed by the Security Operations Center (SOC) Supervisor or Watch Commander.
  • Must display a thorough work process ensuring that each and every step in a critical process is completed.
  • Must be able to fill in the position of Security Officer when operational needs dictate

Company Size

10,001+

Company Stage

N/A

Total Funding

N/A

Headquarters

Palo Alto, California

Founded

2012

Simplify Jobs

Simplify's Take

What believers are saying

  • Alameda Health System partnership expands specialized care access for 400,000 Alameda residents.
  • Retrieval Augmented Generation ensures accurate, hallucination-free clinical responses.
  • EHR training modernization cuts onboarding time 50% and boosts clinician retention.

What critics are saying

  • Epic's AI-native EHR upgrades outperform ChatEHR, eroding Stanford's advantage in 12-18 months.
  • St. Rose Hospital collaboration taints Stanford's brand with safety-net operational liabilities.
  • California Public Health halts ChatEHR expansion after FURM bias audit failures in 18-24 months.

What makes Stanford Health Care unique

  • ChatEHR embeds generative AI directly into Epic EHR for 40-70% faster workflows.
  • MedHELM provides continuous real-time evaluation of AI model safety and accuracy.
  • DAX Copilot AI scribe automates notes, enabling clinician eye contact with patients.

Help us improve and share your feedback! Did you find this helpful?

Your Connections

People at Stanford Health Care who can refer or advise you

Benefits

Health Insurance

Paid Vacation

401(k) Retirement Plan

Flexible Work Hours

Remote Work Options

Wellness Program

Mental Health Support

Company News

PR Newswire
Mar 31st, 2026
LogicSource achieves 104% revenue growth, named to New England's fastest-growing companies 2026 list

LogicSource, a procurement services and technology provider, has been named to The Boston Globe and Statista's New England's Fastest-Growing Companies 2026 list. The company achieved 104% revenue growth during the recognition period whilst expanding its workforce by 20%. Based in Westport, Connecticut, LogicSource completed 40,000 sourcing events annually for clients using its OneMarket technology platform, which now holds over $200 billion in cross-industry spend benchmarks. The company focuses on indirect procurement across categories including marketing, logistics, packaging and facilities. LogicSource serves clients such as lululemon, Tractor Supply Co., and Stanford Healthcare. The ranking, published by The Boston Globe in partnership with Statista, evaluates businesses based on sustained revenue growth and operational scale.

Amplifire
Mar 26th, 2026
Stanford Health Care Took the Stage at HIMSS to Share Their EHR Training Success

Stanford Health Care took the stage at HIMSS to share their EHR training success. Amplifire + Kahuna Partnership were honored to see this work come to life during Stanford Health Care's presentation at HIMSS Global Health Conference & Exhibition last week. Anne Hyland, Vice President of EHR Learning, and Michael Walker, Senior Director of New Business at Amplifire, were able to hear first-hand how their team handled the challenges and the measurable outcomes they've achieved. It was a powerful reminder of what's possible when innovation is paired with a clear focus on outcomes. What stands out most is Stanford Health Care's thoughtful approach to modernizing onboarding. Rather than accepting traditional, one-size-fits-all training, they've embraced a more personalized, data-driven model that meets clinicians where they are, respecting prior experience while ensuring mastery of critical workflows. The result is not only greater efficiency, but a more confident, prepared workforce ready to deliver high-quality care from day one. As highlighted in their broader work, this approach has also enabled earlier identification of struggling learners and more targeted support, ultimately strengthening both performance and satisfaction. Stanford Health Care continues to set the standard for innovation in workforce development, and their recent feature in Healthcare IT News highlights just how impactful that work has been. By reimagining EHR training, their team has successfully reduced training time by 50% while simultaneously improving learning retention, an achievement that speaks to both their strategic vision and deep commitment to clinician success. Congratulations to the entire Stanford Health Care team on this well-deserved recognition. Their leadership is not only advancing their own organization, but helping to shape the future of healthcare workforce development across the industry.

ODBMS.org
Nov 17th, 2025
Nikesh Kotecha on Blueprint for Trust: How ChatEHR Establishes a Framework for Responsible AI in Clinical Care

Nikesh Kotecha on blueprint for trust: how ChatEHR establishes a framework for Responsible AI in clinical care. Stanford Health Care, part of Stanford Medicine, was awarded a 2025 InterSystems Impact Award for its AXIOM initiative for fast access to electronic health records. In turn, AXIOM underpins the ChatEHR medical chatbot that Nikesh Kotecha, head of the Data Science team at Stanford Health Care, presents below. The Impact Award recognizes the work of the team to deliver low-latency, comprehensive access to patient data from complex electronic health record (EHR) systems. This foundation has been essential to enabling the ChatEHR platform. Contribution by Nikesh Kotecha The integration of Large Language Models (LLMs) into health systems holds the promise of reducing administrative burden and cognitive overload for clinical teams. However, deploying such tools in clinical workflows requires a commitment to safety, governance, and continuous monitoring. Stanford Medicine's ChatEHR platform, an initiative developed as part of an enterprise investment in establishing a Data Science pillar, serves as an essential case study for any health system aiming for responsible AI adoption. Setting up a responsible clinical AI system requires focus on three key areas: a robust platform architecture, transparent governance, and continuous evaluation. A significant barrier to integrating AI tools into clinical workflows is often fragmented data sources and latency in data access. Traditional reporting systems were unsuitable for the real-time applications needed at the point of care. The ChatEHR Platform tackles this with a sophisticated, four-pillar architecture: * LLM Router: Provides secure access to a variety of models, standardizing calls and handling centralized logging. * Real-Time Data Access: Fetches and organizes clinical information using Fast Healthcare Interoperability Resources (FHIR). This enables near real-time responsiveness by combining FHIR and HL7v2 messaging with optimized query performance. * Function Server: Transforms generic AI capabilities into healthcare-specific functions and task-specific endpoints, powering workflow automations. * EHR Integration: Manages secure connections and integrates the custom UI directly into Epic Hyperspace, maintaining authentication and patient context. This scalable architecture, underpinned by Stanford's AXIOM framework, proved critical for performance. For instance, the system cut retrieval times by over 95% - from nearly two minutes to four seconds - for some AI workflows. This focus on low-latency data access is fundamental to clinical decision-making and the AXIOM initiative, which provides this breakthrough data capability, was recognized as an InterSystems Impact Award winner in 2025. Responsible AI deployment starts with organizational frameworks and strong governance models. ChatEHR is explicitly guided by Stanford Medicine's Responsible AI Lifecycle. Oversight is managed through the Data Science Executive Committee (DSEC), ensuring transparency and alignment throughout the project life cycle. Furthermore, all system operations adhere to HIPAA and HITECH standards, utilizing role-based access controls inherited directly from the EHR to limit data exposure. This structured approach ensures that AI deployment is treated not as a one-off technical build, but as a governed, enterprise-wide strategy. Crucial to maintaining trust and safety is developing approaches for evaluating LLM performance, a task made challenging by the flexibility and variability of generative AI outputs.ChatEHR implemented MedHELM (Medical Holistic Evaluation of Language Models), a generative AI evaluation framework developed in collaboration with the Stanford Center for Biomedical Informatics Research (BMIR) and the Institute for Human-Centered AI (HAI) By combining governance, an embedded platform for low-latency data access, and monitoring via the MedHELM framework, the ChatEHR initiative provides a replicable blueprint for health systems seeking to translate AI innovation into measurable clinical and operational impact while upholding standards of safety and responsibility. Nikesh Kotecha, Head of Data Science at Stanford Health Care, tasked with building a group to develop and deploy AI-guided models into clinical and operational workflows. Prior to that, Nikesh started and led the informatics efforts at the Parker Institute for Cancer Immunotherapy, a non-profit organization bringing together 7 top cancer centers Organization: Stanford Health Care Stanford Health Care's AXIOM initiative (Advance Extraction for Intelligent Orchestration and Medical Insight) is a transformative solution that enables fast access to complex electronic health record (EHR) data. Using a unique recursive data retrieval method, AXIOM minimizes duplication and reduces query times from minutes or hours to seconds. It leverages a FHIR (Fast Health Interoperability Resources) repository on InterSystems IRIS, to power advanced AI and large language model (LLM) applications. This architecture enables real-time clinical insights, enhances care team collaboration, and supports use cases such as augmented triage and optimized patient flow across a variety of care settings. Sponsored by InterSystems and selected by an independent panel of judges from Massachusetts Institute of Technology (MIT).

American Heart Association
Sep 24th, 2025
Stanford section chief of preventive cardiology to receive the 2025 Joseph A. Vita Award

Stanford section chief of preventive cardiology to receive the 2025 Joseph A. Vita Award.

Leo Cancer Care
Sep 18th, 2025
What's on for Leo Cancer Care at ASTRO 2025

Stanford Health Care will host Modern Proton Radiation Oncology, featuring an exclusive tour of their new treatment room equipped with the MEVION S250-FIT system integrated with Leo Cancer Care's Marie solution.