AI Operations Engineer

Cisco; Bengaluru; On-site; INR 2,500,000 - 5,500,000; Full time

Job summary

Cisco in Bengaluru is seeking an AI Engineer to design, build, and operate autonomous agentic workflows powering commerce operations. You will translate ambiguous requirements into reliable multi-step agent workflows, orchestrating LLM reasoning, tool calling, retrieval, and enterprise integrations across platforms and time zones.

You will own the full lifecycle of LLM-powered applications, deploy and monitor in production, and collaborate with cross-functional AI teams to deliver scalable,

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, AI/ML, or a related field.
• 5+ years of advanced proficiency in Python and SQL with production-grade data/AI experience.
• Deep knowledge of Snowflake Data Cloud, especially Cortex AI functions.
• 2+ years of experience building and deploying LLM-powered or agentic AI applications.
• Strong Python and hands-on with LLM/agent frameworks (LangChain, LangGraph, AutoGen, CrewAI, OpenAI/Anthropic SDKs).
• Experience with CI/CD practices, Git, and automated testing in an enterprise environment.

Responsibilities

• Architect and build production AI agents, including multi-agent and human-in-the-loop workflows.
• Design robust tool calling, planning, and state management.
• Create A2A integrations and interoperability using emerging standards.
• Develop API integrations REST/GraphQL, event-driven and webhook-based services.
• Manage end-to-end lifecycle of LLM-powered applications including deployment and monitoring.
• Build and tune retrieval-augmented generation pipelines and vector databases.
• Implement monitoring for LLM drift, hallucinations, and token usage.
• Optimize Snowflake credit consumption and scale warehouses for cost efficiency.
• Design guardrails and human-in-the-loop gates for sensitive actions and failover.
• Own AI/ML CI/CD pipeline with versioning and progressive rollout.

Skills

Python

SQL

Snowflake Cortex

LLM frameworks

CI/CD

Git

API integrations

LangChain

LangGraph

AutoGen

CrewAI

Education

Bachelor's degree in Computer Science, Data Engineering, AI/ML, or related field

Tools

LangChain

LangGraph

AutoGen

CrewAI

OpenAI SDKs

Anthropic SDKs

Snowflake Cortex

Job description

Meet the Team

Join Cisco's Commerce Intelligence Data & Analytics team, a pivotal group delivering seamless intelligence, advanced analytics, and cutting-edge agentic experiences across our business operations. Our mission is to build a scalable, unified, and AI-ready data foundation that drives high-impact business decisions and automated Agentic actions . As a specialized team of engineers and operational experts, we move beyond traditional maintenance to solve complex, large-scale commerce challenges with agentic AI. We achieve this by blending innovation, deep process knowledge, technical expertise, and a relentless focus on business impact, ultimately enhancing operational efficiency and data-driven decision-making at scale.

Your Impact

As an AI Engineer, you will design, build, and operate the autonomous and semi-autonomous agents that power Cisco's commerce operations. You will translate ambiguous operational requirements into reliable multi-step agent workflows - orchestrating LLM reasoning, tool and function calling, retrieval, and integrations into commerce platforms and operational systems. You will be responsible for the full lifecycle: designing the agent and its guardrails, grounding it with retrieval, connecting it to enterprise systems through robust API and agent-to-agent (A2A) integrations, evaluating its behavior, and deploying and monitoring it in production by collaborating with extended team across various time zones. You will partner with cross-functional AI teams to identify high-value opportunities and deliver intelligent, automated workflows that optimize performance and drive durable growth. This role is a pillar to our operational strategy and to Cisco's AI-first vision.

Responsibilities

• Architect and build production AI agents - including multi-agent and human-in-the-loop workflows - that automate commerce operations. Work in partnership and guidance from the core team at onsite
• Implement agent orchestration with modern frameworks (e.g., LangGraph, LangChain, AutoGen, CrewAI, or equivalent), designing robust tool/function-calling, planning, and state management.
• Build agent-to-agent (A2A) integrations and interoperability using emerging standards and protocols (e.g., A2A, MCP), enabling agents to delegate, coordinate, and hand off work reliably.
• Design and implement API integrations - REST/GraphQL, event-driven and webhook-based services, authentication, rate limiting, and resilient error handling - to connect agents with commerce platforms and enterprise data sources.
• Manage the end-to-end lifecycle of LLM-powered applications using Snowflake Cortex, from model selection and fine-tuning to deployment, versioning, and decommissioning.
• Architect robust agentic workflows using Snowflake Native Apps and Stored Procedures, implementing sophisticated tool-calling, planning, and state management that ensures seamless execution across complex operational tasks.
• Build and tune retrieval-augmented generation (RAG) pipelines over documents, structured data, and knowledge repositories. Implement  and maintain low-latency vector databases, semantic search architectures, and Retrieval-Augmented Generation (RAG) pipelines using native vector data types and search functions.
• Build automated monitoring mechanisms to track LLM drift, hallucination rates, and token usage, triggering self-healing alerts and automated model retraining or routing workflows.
• Proactively manage and optimize Snowflake credit consumption for AI workloads; implement warehouse auto-scaling, query profiling, and multi-cluster strategies to ensure cost-efficiency at scale.
• Design guardrails and human-in-the-loop gates for sensitive actions, and implement LLM routing  and failover for reliability and cost control.
• Apply prompt engineering and context engineering to make agent behavior accurate, safe, and consistent under real operational conditions.
• Own the AI/ML CI/CD pipeline, ensuring rigorous version control, automated testing, and progressive rollout of AI models and agentic workflows across development, staging

A self-starter with proven expertise to deliver outcomes with minimal supervision

Minimum Qualifications

Bachelor's degree in Computer Science, Data Engineering, AI/ML, or a related technical field, equivalent practical experience.

5+ Years of Advanced proficiency in Python and SQL, with proven experience building, testing, and deploying production-grade data and AI solutions.

Deep technical understanding of the Snowflake Data Cloud especially Cortex AI functions and secure data sharing.

2+ years of Proven experience building and deploying LLM-powered or agentic AI applications in production.

Strong proficiency in Python and hands-on experience with LLM/agent frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or the OpenAI/Anthropic SDKs).

Experience with CI/CD practices, version control (Git), and automated testing frameworks in an enterprise environment