Jobs

Program Manager

|  Posted On: Mar 24, 2026

location:Menlo Park, CA 94025

Duration:6 Months, Contract

mode of work:Completely Remote

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Job Summary

Job Title:  
Program Manager
Posted Date:  
Mar 24, 2026
Duration:  
6 Months, Contract
Shift(s):  

08:00 - 16:00 PST

Salary ($): 
80.00 - 85.00 per Hourly (compensation based on experience and qualifications)
We care about you! Explore Rangam’s benefits information

Talk to our Recruiter

Name:
 
Bishwaroopa Singh

Email:
 
Bishwaroopa@rangam.com

Phone:
 
425-264-4490

Description

Product operations analyst / manager

Top 3 must-have HARD skills:

  • Must have several years of AI experience
  • Must have prior product or engineering operations experience
  • Must have prior experience with innovation processes

 

Good to have skills:  

  • Experience in a software or, preferably a hardware company with consumer electronics
  • Strong communication and collaboration skills: go getter personality
  • Prior Client experience is an asset

 

Summary:

  • We are looking for a Technology Operations & AI Automation Program Manager to transform our technology innovation operations.
  • This role manages the end-to-end operational processes that track, report on, and govern our technology portfolio — and then systematically automates those processes using AI.
  • This role will work closely with hardware engineering leads, program managers, product managers, business operations, and finance teams to transform a manual, labor-intensive operations function and make it self-sustaining through intelligent automation.
  • You will start by running the operations, then progressively replace manual workflows with AI-driven pipelines until the process largely runs itself.

 

Minimum Qualifications

  • 5+ years of experience in product or technology operations, engineering operations, or program management in a hardware or technology development environment Demonstrated experience building operational automation using AI/LLM tools (e.g., building AI agents, writing prompts and skills for LLM-based workflows, or deploying AI-assisted data pipelines)
  • Experience designing data flows from intake to output — forms, databases, dashboards, and automated reports Track record of driving process adoption across engineering or cross-functional teams Strong communication skills
  • Ability to translate operational data into actionable insights for both engineering teams and senior leadership Self-directed work style with comfort owning an entire operational domain independently

Preferred Qualifications

  • Experience with stage-gate or milestone-based technology development processes (e.g., NPI, technology readiness levels, innovation pipelines) Familiarity with Client's internal tools and workflows
  • Experience with portfolio management, budget forecasting, or program operations at scale in a hardware
  • R&D organization Hands-on experience with AI application platforms, no-code/low-code database tools (e.g., AppSheet, Airtable), or AI-native development environments Background in wearable devices, AR/VR, consumer electronics, or related hardware domains

Job Day-to-Day Responsibilities

  • Maintain and Automate Core Operations: Maintain and execute the existing operational process for a portfolio of 15–20 active technology innovation projects, using this hands-on execution to thoroughly document and prepare all existing workflows (including progress tracking, milestone reporting, stakeholder updates, and executive dashboards) for subsequent AI-driven automation.
  • Design & Build the Automation Core: Architect, develop, and deploy AI-powered automation pipelines to systematically replace manual operational workflows (e.g., data reconciliation, status tracking, and report generation) for the technology innovation portfolio.
  • Drive process adoption: Champion adoption of new automated processes across cross-functional hardware engineering teams, ensuring that new workflows are used effectively
  • Deliver AI-generated insights: Provide leadership with regular, AI-generated insights on portfolio health, engineering investment efficiency, technology success rates, and resource forecasting