AI Engineer – 5G RAN Analytics & Root Cause Analysis (Senior Technical Lead) at Parallel Wireless

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 validate 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 junior 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 causation • 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 • Demonstrated ability to bridge deep domain knowledge with AI systems engineeringWhat 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.