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OpenAI

Connectivity Software Engineer, Consumer Devices

San Francisco, California, United States

Location
San Francisco, California, United States
Work
Hybrid
Employment
Full-time
Level
Not stated
Function
Engineering
Pay
$347K – $385K a year
Posted
12 months ago

About the role

About the Team

The Connectivity Software Engineering team is responsible for enabling seamless, secure, and high-performance wireless connectivity across OpenAI’s products. We design and optimize Bluetooth, BLE, Wi-Fi, and emerging wireless technologies to ensure robust device pairing, network performance, and interoperability. Our work spans kernel drivers, system services, and user-level tools, with a focus on real-world performance, scalability, and reliability.

About the Role

OpenAI is seeking a Connectivity Software Engineer to design, implement, and optimize wireless connectivity features across our product ecosystem. You’ll work at the intersection of systems software, wireless standards, and hardware integration—building robust pairing and provisioning flows, debugging low-level protocols, and driving performance under real-world RF constraints. You will also support certification, field interoperability, and fleet-scale connectivity infrastructure.

This role is based in San Francisco, CA. We use a hybrid work model of 4 days in the office per week and offer relocation assistance to new employees.

In this role, you will

  • Design, implement, and debug Bluetooth/BLE and Wi-Fi features across kernel drivers, BlueZ/wpa_supplicant/hostapd, and systemd/D-Bus services
  • Deliver robust pairing, bonding, and provisioning flows (GATT/GAP, LE Audio/LC3, WPA3/802.1X, captive portals, NAN)
  • Optimize link performance: throughput, latency, jitter, roaming, coexistence (BT↔Wi-Fi), and power modes (TWT, WoWLAN)
  • Build reliable network management using NetworkManager/nmcli, nl80211/cfg80211/mac80211, DNS/DHCP/mDNS, P2P/SoftAP
  • Instrument and analyze with packet captures and tooling (btmon/hcidump, Wireshark, iperf, eBPF/perf, spectrum sniffers)
  • Drive interoperability and certification readiness (Bluetooth SIG, Wi-Fi Alliance) and resolve field issues with root-cause fixes
  • Contribute to OTA-safe configuration, telemetry, and diagnostics for fleet-scale operation

You might thrive in this role if you

  • Have deep experience shipping wireless features on Linux-based products
  • Are highly proficient in C/C++ with scripting experience (Python or shell) and systems debugging (gdb, strace, logs, packet traces)
  • Possess deep knowledge of Bluetooth Classic/BLE (HCI, L2CAP, GATT/GAP, profiles) and Wi-Fi (802.11 a/b/g/n/ac/ax, WPA2/3, nl80211, NAN)
  • Bring hands-on experience with BlueZ, wpa_supplicant/hostapd, NetworkManager, and driver bring-up on ARM64 or x86 platforms
  • Have a proven track record of improving real-world performance and reliability under RF constraints

Preferred qualifications

  • Experience with LE Audio (LC3), BLE Mesh, advanced roaming (802.11k/v/r), QoS/WMM, multicast/IGMP
  • Coexistence tuning across radios (BT/Wi-Fi/UWB/mmWave) and antenna/RF fundamentals with test equipment workflows
  • Familiarity with UWB (IEEE 802.15.4z, FiRa) ranging/integration; mmWave/Wi-Gig (802.11ad/ay)
  • Experience with security and provisioning at scale (EAP-TLS, device identity, secure boot, disk/network hardening)
  • Background in building factory test, interoperability, and certification test plans; upstream/open-source contributions

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Source

Posted by OpenAI on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 00:15 UTC; the original is the reference.

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