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Technical Lead, Stack

Parallel Wireless Bangalore, Indien
Full-time Hybrid work

Publication date: 30/08/2026

Location Bangalore

Qualifications & required skills-
Understanding of end-to-end solutions for 4G/5G network architecture.
Familiar with 3GPP RAN and O-RAN specifications and functionality.
Development experience on Cellular Radio products complying with 3GPP specifications for E-UTRA (LTE) and NR.
Familiar with communication interfaces: Ethernet / TCP/IP / UDP.
Good knowledge of RAN protocols and interfaces:
LTE/5G AS protocol layers — PHY, MAC, RLC, PDCP, RRC.
Expert-level proficiency in the MAC and RLC layers is required
Knowledge of AI/ML concepts and their application to RAN (e.g., network optimization, ML frameworks); hands-on experience applying AI/ML in a telecom/RAN context is a strong plus.

What you will do
- You will be responsible for the full development process of L2/L3 embedded protocol stack including design, coding, unit testing, debugging, and integration.

- As a stack SW developer, you will develop new features/environment for Parallel Wireless future products and debug existing solutions which are used by our customers around the world.

Responsibilities

You will be responsible for the full development process of L2/L3 embedded protocol stack including design, coding, unit testing, debugging, and integration; As a stack SW developer, you will develop new features/environment for Parallel Wireless future products and debug existing solutions which are used by our customers around the world

Requirements

Understanding of end-to-end solutions for 4G/5G network architecture; Familiar with 3GPP RAN and O-RAN specifications and functionality; Development experience on Cellular Radio products complying with 3GPP specifications for E-UTRA (LTE) and NR; Familiar with communication interfaces: Ethernet / TCP/IP / UDP; Good knowledge of RAN protocols and interfaces: LTE/5G AS protocol layers — PHY, MAC, RLC, PDCP, RRC; Expert-level proficiency in the MAC and RLC layers is required

Nice to have

Knowledge of AI/ML concepts and their application to RAN (e.g., network optimization, ML frameworks); hands-on experience applying AI/ML in a telecom/RAN context is a strong plus
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