GenAI Engineer: RAG Pipelines & Production ML Ops

Robotic Technologies Automation; Palo Alto (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

ROBOTIC PROCESS AUTOMATION LLC is seeking an AI/ML engineer to build GenAI-powered network troubleshooting tools. You will design RAG pipelines, grounding with citations, and productionize models with CI/CD and robust testing.

This role collaborates across data engineering, security, and platform teams to deliver reliable, scalable solutions and measurable improvements in MTTR and accuracy. The ideal candidate has 3–5 years in AI/ML engineering, strong Python/SQL skills, and hands-on experience

Qualifications

• BS/MS in CS, EE, DS or related field; 3–5 years of production ML/AI experience.
• Strong Python and SQL skills with large telemetry datasets.
• Experience with Azure data/AI services and serverless compute.

Responsibilities

• Build, deploy, and operate GenAI-powered tools for network troubleshooting with citations.
• Design and implement RAG pipelines (chunking, embeddings, vector search, grounding).
• Ship reliable services with CI/CD, tests, canaries, and SLOs for accuracy, latency, and cost.
• Implement evaluation harnesses, drift detection, and cost controls.
• Integrate with internal systems and dashboards to close the loop from detection to remediation.
• Collaborate with cross-functional teams to drive measurable MTTR reductions and quality improvements.

Skills

Python

SQL

Azure services

CI/CD

MLOps

Telemetry

RAG

LangChain

Education

BS/MS in CS/EE/Data Science

Tools

Azure Functions

Azure DevOps

Git

Model Registry

Vector databases

Semantic Kernel

LangChain

Job description

ROBOTIC PROCESS AUTOMATION LLC is seeking an AI/ML engineer to build GenAI-powered network troubleshooting tools. You will design RAG pipelines, grounding with citations, and productionize models with CI/CD and robust testing.

This role collaborates across data engineering, security, and platform teams to deliver reliable, scalable solutions and measurable improvements in MTTR and accuracy. The ideal candidate has 3–5 years in AI/ML engineering, strong Python/SQL skills, and hands-on experience