AI Operations Engineer

Cisco Systems · Hardware & Semiconductors

Bangalore, India
On-site
Posted 9 days ago
Data & AI

About the job

Meet the Team

Join Cisco’s Commerce Operations Engineering Center (COEC) as an AI Operations Engineer. You will be part of a collaborative team developing AI-powered automation solutions. Working with AI, engineering, and operations teams, you will help translate operational requirements into reliable and scalable AI solutions that support Cisco’s AI-first future.

Your Impact

As an AI Operations Engineer in COEC, you will contribute to building and supporting AI agents that improve Cisco’s Commerce Operations. You will help develop automated workflows using LLM reasoning, tool and function calling, retrieval, enterprise integrations, and agent-to-agent communication.

Under the guidance of senior engineers and technical leads, you will participate across the AI solution lifecycle, including development, integration, testing, deployment, monitoring, and continuous improvement. Your work will help reduce manual effort, improve operational speed and accuracy, and strengthen the user experience.

What You’ll Do

Develop and enhance AI agents that automate manual and repetitive Commerce Operations tasks.

Implement agent workflows using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or equivalent.

Support agent-to-agent integrations using standards such as A2A and MCP.

Develop secure API integrations with commerce platforms and enterprise data sources using REST, GraphQL, webhooks, and event-driven services.

Apply authentication, rate limiting, validation, and error-handling practices to system integrations.

Build and maintain retrieval-augmented generation (RAG) pipelines using documents, structured data, and enterprise knowledge repositories.

Implement defined guardrails, human approval steps, LLM routing, and failover mechanisms.

Apply prompt and context engineering techniques to improve the accuracy, safety, and consistency of AI-generated outcomes.

Contribute to evaluation and observability capabilities, including test datasets, tracing, audit logging, monitoring, and quality regression detection.

Support deployment and production operations through CI/CD, version control, monitoring, rollback processes, and cost tracking.

Monitor AI solution performance and help report business outcomes using metrics such as efficiency gains, cycle-time reduction, incident reduction, and operational accuracy.

Troubleshoot issues and continuously improve AI workflows, tools, and development practices.

Collaborate with Commerce Operations, application development, infrastructure, and business teams to integrate AI solutions into existing systems and workflows.

Document technical designs, integrations, test results, and operational procedures.

Minimum Qualifications

3+ years of experience in software engineering, AI engineering, data engineering, or a related field.

Experience developing LLM-powered, machine-learning, or automation applications.

Proficiency in Python and experience with one or more LLM or agent frameworks, such as LangChain, LangGraph, AutoGen, CrewAI, OpenAI SDK, Anthropic SDK, or equivalent.

Working knowledge of retrieval-augmented generation, prompt engineering, tool or function calling, and workflow orchestration.

Experience developing API and system integrations using REST, GraphQL, event-driven services, authentication, or enterprise data sources.

Familiarity with software development practices, including Git, testing, debugging, code reviews, and CI/CD.

Ability to solve technical problems and collaborate effectively with business and engineering teams.

Preferred Qualifications

Familiarity with agent interoperability standards and protocols, including A2A, Model Context Protocol (MCP), and OpenAPI-based tool integration.

Exposure to multi-agent systems, human-in-the-loop workflows, and AI agent guardrails.

Experience with evaluation and observability tools such as LangSmith, Langfuse, tracing tools, evaluation harnesses, or equivalent AgentOps/LLMOps platforms.

Knowledge of vector databases and retrieval methods, including semantic search, hybrid search, reranking, or knowledge-graph grounding.

Familiarity with AI governance and safety practices, including role-based access control, audit logging, PII handling, and controls for automated actions.

Experience with cloud platforms such as AWS, GCP, or Azure.

Exposure to MLOps or LLMOps practices, including model deployment, monitoring, version management, and cost tracking.

Understanding of commerce platforms, commerce operations, supply chain operations, or related business processes.

Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field, or equivalent practical experience.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Disclaimer

To ensure that we hire the best talent in the right way, we follow a strict hiring process and recently, Cisco has been made aware of fraudulent recruiters claiming to be from the company. Please be advised that any communication from Cisco about careers will:

be in direct response to an application you have submitted through the company career site

begin with screening or an interview

originate from a Cisco email address, and

be conducted across email, phone, or WebEx

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