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

Parallel Wireless · Bangalore · Onsite

Mixed hiring record · median 53 days open

100100

Hiring signal

Actively hiring

Still listed on the employer's own board · How we score

All reasons
  • 33% of this employer's openings are over 60 days old

In its favour

  • Still listed on the employer's own board

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Technical Lead, Production Dev (QA Automation (AI & Root Cause Analysis) at Parallel Wireless. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

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

Must-have

  • 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

Good to have

  • 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.

Skills

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