Endpoint Engineer

Job Description

The Endpoint Engineer is responsible for the design, implementation, and ongoing management of the organizations device ecosystem. This role focuses on automating the lifecycle of hardware and virtual desktops to ensure a seamless, secure, and "zero-touch"experience for our global workforce. You will serve as the subject matter expert for Apple and Windows management and our cloud desktop infrastructure.


Technical Environment:
Apple (macOS & iOS): Jamf Pro
Windows & Android: Microsoft Intune / Endpoint Manager
Virtual Desktop: Amazon WorkSpaces (AWS)
Scripting: PowerShell, Bash, Python


Key Responsibilities
1. Unified Endpoint Management (UEM)

• Daily Operations: Perform daily upkeep, system maintenance, and regular patch management for all managed endpoints to ensure security and stability.
• Service Desk Escalation: Serve as the final point of contact and subject matter expert for service desk escalations related to complex endpoint issues.
• Apple Fleet: Architect and maintain the Jamf Pro environment for all macOS and iOS devices. Manage configuration profiles, policies, and patch management.
• Windows & Android: Lead the administration of Microsoft Intune, ensuring robust policy application, security baselines, and application delivery.
• Provisioning: Manage Apple Business Manager (ABM) and Windows Autopilot to deliver a true zero-touch deployment experience.

2. Virtual Desktop Infrastructure (VDI)

• Administer and optimize Amazon WorkSpaces.
• Manage WorkSpaces directories, custom bundles, and image creation/maintenance.
• Troubleshoot connectivity and performance issues within the AWS ecosystem.

3. Automation & Engineering

• Develop and maintain sophisticated scripts in PowerShell and Bash to automate manual tasks and integrate system APIs.
• Build and maintain a library of packaged software (dmg, pkg, msi) for silent deployment.
• Implement automated reporting for hardware inventory, license compliance, and security auditing.

4. Security & Compliance

• Enforce endpoint security standards, including FileVault/BitLocker encryption and EDR agent health.

• Partner with Security teams to remediate vulnerabilities across the endpoint fleet.

Required Qualifications:

• Experience: Minimum 35 years in an Endpoint Engineering or MDM-focused role.
• amf Mastery: Proven experience managing both macOS and iOS at scale via Jamf Pro.
• Intune Proficiency: Experience managing Windows environments through Microsoft Endpoint Manager.
• VDI Expertise: Hands-on experience with Amazon WorkSpaces administration.
• BYOD Deployment: Experience deploying and managing a Bring Your Own Device (BYOD) program for personal mobile phones (iOS/Android).
• Advanced Scripting: Ability to write and debug Bash and PowerShell scripts from scratch.
• Identity: Understanding of Okta or Azure AD (Entra ID) as it relates to device enrollment and SSO.

Education & Certifications:

• Bachelors degree in Computer Science, IT, or equivalent professional experience.
• Relevant certifications (e.G., Jamf 200/300, Microsoft MD-102, or AWS Certified Cloud Practitioner) are a plus.
• Bonus: AI Tool Deployment Experience

As client continues to expand its AI-powered workforce tooling, experience deploying and managing enterprise AI tools is a strong differentiator for this role. Candidates with hands-on experience rolling out any of the following will stand out:


Enterprise AI Search & Knowledge Tools
Experience deploying Glean or similar AI-powered enterprise search platforms, including connector configuration, SSO integration (Okta/Azure AD), and end-user onboarding at scale.


Agentic AI Coding Tools
Familiarity with deploying Claude Code or GitHub Copilot to engineering teams including managing licensing, IDE plugin distribution via MDM (Jamf/Intune), and API key or credential management through secure vaulting solutions.

AI Productivity & Workflow Automation Tools
Experience rolling out AI desktop or productivity agents such as Claude Cowork, including packaging and silent deployment, managing update cadences, and coordinating with IT Security to ensure compliance with data handling policies.

General AI Deployment Best Practices
Understanding of the endpoint and identity considerations unique to AI tools: network allowlisting for LLM API endpoints, DLP policy tuning for AI-generated content, user provisioning workflows, and communicating rollout plans across IT, Security, and end-user teams.


Meet Your Recruiter

Manoj Patidar