AI Platform Engineer — CPQ & LLM Infra

Cisco Systems, Inc

San Jose (CA)

Hybrid

USD 131,000 - 166,000

Full time

6 days ago
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Job summary

Cisco Systems, Inc. is seeking a Technical Systems Engineer within the Commerce Product Management & Engineering team to sustain, monitor, and troubleshoot critical AI-enabled capabilities and LLM platform infrastructure.

You will bridge core AI, platform engineering, and end users, resolving complex operational issues across RAG pipelines and model endpoints. In a hybrid setup, you will collaborate on multi-functional projects, analyze processes and data, and implement new capabilities with

Qualifications

  • Bachelor’s degree in Engineering and 6–7 years of relevant experience.
  • 3+ years in using or supporting Java, SQL, PL/SQL, Oracle, MongoDB, Snowflake, AngularJS, Python, APIs, Elastic, or Kibana.
  • 3+ years in Technical Support, SRE, Software Engineering, with 1–2 years in AI/ML or LLM-driven apps.

Responsibilities

  • Act as main contact for production support across business units.
  • Primary escalation point for AI assistants and foundational AI capabilities.
  • Triage, debug, and resolve incidents related to model latency and prompt drift.
  • Monitor workflows and orchestration layers to maintain high availability and SLAs.
  • Debug and maintain Python-based AI frameworks, microservices, and REST endpoints.
  • Develop automation scripts and health-check utilities in Python.
  • Monitor AI telemetry and latency metrics using observability platforms.
  • Document processes, resolutions, and recurring issues for training.

Skills

Java
SQL
PL/SQL
Oracle
MongoDB
Snowflake
AngularJS
Python
APIs
Elastic
Kibana

Education

Bachelor’s degree in Engineering

Tools

Datadog
Splunk
Langfuse
LangSmith

Job description

Cisco Systems, Inc. is seeking a Technical Systems Engineer within the Commerce Product Management & Engineering team to sustain, monitor, and troubleshoot critical AI-enabled capabilities and LLM platform infrastructure.

You will bridge core AI, platform engineering, and end users, resolving complex operational issues across RAG pipelines and model endpoints. In a hybrid setup, you will collaborate on multi-functional projects, analyze processes and data, and implement new capabilities with

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