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For Employers

AI Engineer

Parallelstack Sytems

12 - 16 years

30 - 35 Lacs

bengaluru

Posted:1 day ago| Platform:

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Skills Required

rca rrc pdcp debugging hypothesis testing scheduling mimo distribution system analytics python

Work Mode

Work from Office

Job Type

Full Time

Job Description

AI Engineer - 5G RAN Analytics & Root Cause Analysis (Senior Technical Lead)

Role Overview

We are looking for a mid-senior level AI Engineer / Technical Lead (12-16 years overall experience) to architect and build next-generation AI agents for automated Root Cause Analysis (RCA) in our 5G RAN product .

In this role, you will lead the development of agentic AI systems that consume high-volume, high-velocity telecom telemetry data logs, traces, metrics, events, and KPIs and autonomously identify, reason about, and explain network issues across the LTE and 5G RAN stack.

This is a hands-on, deeply technical role at the intersection of AI systems engineering, large-scale data engineering, and LTE/5G RAN domain expertise .

What you will do

Key Responsibilities

AI & Agent Architecture
Design and implement AI agents for automated RCA across LTE / 5G RAN systems.
Build tool-using, reasoning-capable agentic workflows (multi-step analysis, hypothesis testing, causal reasoning).
Develop AI pipelines that analyze logs, traces, metrics, events, alarms, and KPIs to detect anomalies and infer root causes.
Architect RAG and Graph-RAG based knowledge systems grounded in:
Telecom specifications (3GPP)

Product documentation

Historical incidents, playbooks, and RCA reports
Context Engineering & Knowledge Systems
Lead context engineering for LLM-based systems (prompt structure, memory, grounding, retrieval boundaries).
Design knowledge graphs / causal graphs representing RAN components, signal flows, KPIs, and failure modes.
Build explainable AI outputs human-readable RCA narratives suitable for field engineers and domain experts.

Data Engineering at Telecom Scale

Build and optimize telemetry ingestion pipelines handling terabytes of data:
eNB/gNB logs (MAC, PHY, RLC, PDCP, RRC, scheduler, FAPI)
Distributed traces
Metrics & time-series KPIs
Implement scalable processing using batch + streaming paradigms.
Ensure performance, correctness, and cost efficiency for near-real-time analytics.
Domain-Driven RCA
Encode LTE & 5G RAN domain knowledge into AI-driven analysis:
Air-interface failures
Scheduling issues
HARQ/BLER/throughput anomalies
Mobility, latency, call drop, and QoE degradation
Collaborate closely with RAN system engineers and field teams to vali AI diagnoses.
Technical Leadership
Act as technical lead / architect for AI-driven observability and RCA initiatives.
Perform design reviews, set engineering best practices, and mentor ior engineers.
Influence product roadmap for AI-native network analytics.

what you must have

Expert Python programmer (production-grade, scalable systems).
Strong data engineering expertise :
Large-scale log processing
Time-series analytics
Distributed systems
Deep hands-on experience building AI agents (tool-calling, planning, reasoning).
AI / ML / LLM Systems
Deep experience with:
RAG systems
Graph-RAG / Knowledge-Graph-based retrieval
Context engineering and prompt design
Experience integrating LLMs into real production systems .
Strong understanding of statistics, probability, and data science fundamentals :
Anomaly detection
Correlation vs cau ion
Signal vs noise in noisy telemetry streams
Telecom Domain (Highly Desirable)
Strong working knowledge of LTE and/or 5G RAN :
MAC, PHY, RLC, PDCP, RRC layers
Scheduler behavior, HARQ, MIMO, CA, mobility
Experience analyzing RAN logs, traces, KPIs, and counters .
Familiarity with 3GPP specifications is a major plus.

Preferred Skills

Experience building AI-driven RCA or observability platforms .
Knowledge of causal inference frameworks or graph-based reasoning.
Experience with streaming platforms (Kafka, Flink, Spark, etc.).
Experience deploying AI systems in cloud-native environments .
Exposure to telecom field deployments or live network debugging .

Experience Level

12-16 years overall experience
Prior experience as a Senior Engineer / Technical Lead / Architect
De strated ability to bridge deep domain knowledge with AI systems engineering

What Makes This Role Unique

Opportunity to build AI agents that truly reason , not just dashboards or shallow analytics.
Direct impact on next-gen autonomous 5G RAN operations .
Work on some of the hardest data problems in the telecom domain .
Shape the future of AI-native RCA for large-scale communication networks .

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