1 day ago
Bengaluru, IndiaSenior
Responsibilities
- Design and build AI agents that automate manual and repetitive Commerce Operations tasks.
- Implement agent orchestration and agent-to-agent integrations using frameworks and standards such as LangGraph, LangChain, AutoGen, CrewAI, A2A, and MCP.
- Build secure integrations with commerce platforms and enterprise data sources using REST, GraphQL, webhooks, event-driven services, authentication, rate limiting, and error handling.
- Develop and optimize RAG pipelines using documents, structured data, and knowledge repositories.
- Implement guardrails, human approval gates, LLM routing, failover mechanisms, prompt engineering, and context engineering.
- Build evaluation and observability capabilities including offline test sets, online monitoring, tracing, audit logging, and quality regression detection.
- Own production deployment and operations, including progressive rollout, rollback, monitoring, model and version control, and cost tracking.
- Measure AI solution performance and report business impact through efficiency, cycle-time, incident, and accuracy metrics.
- Partner with Commerce Operations, application development, infrastructure, and business teams to integrate AI solutions into existing workflows.
Requirements
- 7+ years of experience in software engineering or a related field within an enterprise environment.
- Production experience building and deploying LLM-powered or agentic AI applications.
- Strong Python skills and practical experience with LLM and agent frameworks such as LangChain, LangGraph, AutoGen, CrewAI, OpenAI SDK, or Anthropic SDK.
- Expertise in RAG, prompt engineering, tool and function calling, agent orchestration, and multi-agent communication or workflow orchestration.
- Experience with REST, GraphQL, event-driven services, authentication, APIs, and enterprise data integrations.
- Ability to lead technical delivery and collaborate with multifunctional business and engineering teams.
- Preferred experience with A2A, MCP, OpenAPI-based tool integration, multi-agent systems, human-in-the-loop workflows, and agent guardrails.
- Preferred experience with evaluation and observability tools such as eval harnesses, tracing, LangSmith, Langfuse, or equivalent AgentOps/LLMOps platforms.
- Preferred knowledge of vector databases, hybrid search, reranking, multimodal retrieval, and knowledge-graph grounding.
- Preferred familiarity with AI governance, RBAC, audit logging, PII handling, high-risk action controls, cloud platforms, MLOps/LLMOps, and FinOps.
- Advanced degree in AI, Machine Learning, Computer Science, or a related field is preferred.
Tech Stack
Categories
About Cisco
Cisco designs and sells networking, security, and collaboration platforms for enterprises, service providers, and governments, spanning routers and switches, Wi‑Fi, firewalls, zero‑trust, observability, and cloud-managed IT (Meraki) plus Webex. Its business model mixes hardware, software subscriptions, and support/consulting services. Founded in 1984 and headquartered in San Jose, California, Cisco is a public company traded on Nasdaq and serves customers across data centers, campuses, and service provider networks.