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Open nowPosted 16 hours ago

Technical Lead, Production Dev (QA Automation (AI & Root Cause Analysis)

Parallel Wireless47 open roles

Where
Bangalore
Work mode
On site
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Your applicationOpen nowTechnical Lead, Production Dev (QA Automation (AI & Root Cause Analysis)Parallel Wireless · Bangalore
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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. Parallel Wireless postings stay open a median of 37 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: posted 16 hours ago

Parallel Wireless median: 37 days open

The posting

What you will do

  • Integration/System/E2E Featue Validation of PW products (LTE/NR/GSM)
  • Use AI tools (Claude / AI-assisted engineering) to accelerate code understanding, log analysis, debugging, correlation and RCA — especially on multi-module problems.
  • Identification of the scenarios, enhance the coverage to make the product robust & stabile
  • Analysis of the issue/RCA on field and lab issues that span multiple modules, correlating evidence across the full stack: → UE logs · PHY logs · DU / MAC / SCH logs · CU / L3 logs · Core logs · Platform logs · RRH logs · System logs · field issues across EMS / system monitoring.
  • Reproduce field/customer issues in the lab on production-like setups.
  • Field-issue investigation with direct customer / field involvement; feed learnings back into design, regression and stability.
  • Automation of the E2E features

What we are looking for

  • Solid wireless/telecom system understanding across 2G / 4G LTE / 5G NSA / SA — RRC, S1AP/NGAP, X2/Xn, PDCP/RLC/MAC scheduling, PHY/FAPI, GTP-U, and the core/platform interfaces.
  • Handson experience in Python/Pytest for tools/automation scripting
  • Proven debugging & RCA skills: coredumps/gdb, log/PCAP analysis, memory/crash triage, KPI/counter reasoning.
  • A system mindset — comfortable reasoning across UE ↔ RAN ↔ Core ↔ Platform ↔ EMS rather than a single layer.
  • Willingness and aptitude to work with AI tools as a daily engineering accelerator
  • O-RAN / disaggregated CU-DU, fronthaul (split 7.2), PTP/timing, IPsec/transport exposure.
  • Experience with EMS / OSS, Kibana/KPI monitoring, PM counters.
  • Prior field / customer-facing deployment or NPI experience.
  • Scrum / Agile delivery experience
  • Networking knowledge is an added advantage

Academic Qualification (Education)

  • Bachelor’s (B.E/B.Tech) or Master’s degree (M.E. or M.Tech.) in Electronics/Communication/Computer Science Engineering or equivalent training, education and experience.
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