Pre-Release Operations Engineering E3

ROLE SUMMARY

We are seeking an AI-First Software Development Engineer 3 to join our Pre-Release Operations team supporting the

quality and release readiness of connectivity device software. This is a hands-on builder role at the intersection of AI

engineering and device quality. The engineer will develop intelligent tooling, implement agentic automation, and

integrate AI-driven observability into pre-release workflows while collaborating with senior engineers and cross-

functional teams.

We are looking for engineers who use Claude, ChatGPT, Replit, GitHub Copilot, or custom LLM agents

alongside Python or Shell, and who can build practical AI-assisted workflows that make the quality pipeline

faster, more reliable, and easier to operate.

Hands-on experience in broadband or connectivity device software, embedded systems, triage automation, and

telemetry analysis is valued and should complement this AI-first engineering orientation.

CORE RESPONSIBILITIES

1 · AI-Powered Engineering & Agentic Automation

• Develop and enhance agentic AI workflows that monitor device health, parse failure logs, classify defects, and

generate release readiness signals with reduced manual intervention.

• LLM platforms (Claude, ChatGPT), MCP, Replit, GitHub Copilot — from intelligent log parsers to natural-

language defect summarizers and automated triage bots.

• Contribute to the design and implementation of AI-assisted automation frameworks for test generation, self-

healing scripts, and predictive failure analysis across pre-release pipelines.

• Identify manual, repetitive engineering workflows and automate them using AI-driven pipelines, including

change impact assessment and build qualification.

• Integrate LLM APIs and AI SDKs into existing quality toolchains; prototype rapidly using low-code/no-code AI

environments like Replit or Jupyter.

• Create tools and frameworks that improve defect classification, issue correlation, failure pattern detection, and

build/spin qualification decisions.

• Document tools, workflows, triage playbooks, stability signatures, and operational best practices for repeatable,

scalable execution.

2 · Observability, Monitoring & Intelligent Dashboards

• Develop and enhance telemetry pipelines, dashboards, and automated health checkpoints that surface

actionable quality signals for connectivity device software.

• Improve pre-release monitoring by designing signal-based health checks and AI-generated actionable quality

reports that reduce manual review burden.

• ELK, Grafana, Kibana and extend them with AI-powered insight layers for smarter alerting

3 · Broadband Domain Engineering & Stability Analysis (Good to Have)

• Develop engineering solutions that improve pre-release operational quality for connectivity device software,

including gateways, routers, extenders, and RDK-B platforms.

• Perform technical triage and root cause analysis for pre-release issues related to stability, performance,

endurance, reliability, and operational readiness.

• Analyse device and system behaviour using logs, crash signatures, telemetry, memory/performance indicators,

and platform diagnostics — accelerated by AI-assisted log analysis.

• Support endurance and long-duration test analysis by identifying trends: memory growth, zombie processes,

file leaks, throughput degradation, CPU anomalies, and service instability.

• Review software changes for risk impact, contribute to change assessments, and support release governance

with AI-generated risk summaries.

KEY SKILLS

AI & Automation — Primary Focus

▸ Agentic AI design & multi-step LLM

orchestration

▸ Workflow automation using AI agents

▸ AI tools: Claude, ChatGPT, Replit, GitHub

Copilot

▸ Low-code AI platforms (LangChain, AutoGen,

Replit)

▸ LLM API integration & prompt engineering ▸ AI observability & anomaly detection

▸ AI-powered test & automation framework design ▸ Self-healing automation & predictive analysis

Engineering & Broadband Domain

▸ Python or Shell scripting (Any programming) ▸ CI/CD pipelines (Jenkins, GitHub, Gerrit)

▸ Telemetry pipelines & log analysis ▸ System-level debugging & crash analysis

▸ ELK / Grafana / Kibana monitoring stacks ▸ Dashboard & alerting design

▸ Connectivity device software & RDK-B platforms ▸ Embedded Linux, gateways, routers, extenders

QUALIFICATIONS

Required

• Bachelor’s degree in computer science, Electronics, Engineering, or related field.

• 7+ years of experience in software engineering, test engineering, or device software quality.

• Demonstrated hands-on use of AI tools (Claude, ChatGPT, Replit, Copilot, or similar) to solve real engineering

problems professionally.

• Experience developing or contributing to agentic AI workflows or LLM-integrated automation pipelines.

• Experience with CI/CD quality pipelines using Jenkins, GitHub, or Gerrit.

• Hands-on experience in embedded systems, connectivity device software, or broadband/CPE/gateway

platforms.

• Proficiency in Python or Shell, with experience developing automation, log parsers, or telemetry-based tools.

• Good understanding of Linux-based systems, networking fundamentals, and system resource behavior.

Preferred

• Experience with LangChain, AutoGen, or multi-agent orchestration frameworks.

• Familiarity with RDK-B, broadband gateways, routers, or Wi-Fi platforms.

• Exposure to ELK, Grafana, Kibana, or similar observability stacks.

• Experience in technical triage using system logs, crash dumps, traces, and performance metrics.

• Prior involvement in endurance/reliability testing, defect management, or release readiness reviews.