22 hours ago
Bengaluru, IndiaMid Level
Responsibilities
- Develop and enhance AI agents that automate manual Commerce Operations tasks.
- Implement LLM and agent workflows using frameworks such as LangGraph, LangChain, AutoGen, and CrewAI.
- Build agent-to-agent integrations using A2A and MCP.
- Develop secure integrations with commerce platforms and enterprise data sources using REST, GraphQL, webhooks, and event-driven services.
- Build and maintain retrieval-augmented generation pipelines using documents, structured data, and enterprise knowledge repositories.
- Implement guardrails, human-approval steps, LLM routing, failover mechanisms, and prompt and context engineering.
- Contribute to evaluation, tracing, audit logging, monitoring, and quality-regression detection.
- Support deployment and production operations, including version control, rollback processes, and cost tracking.
- Troubleshoot and continuously improve AI workflows while documenting technical designs, integrations, tests, and procedures.
- Collaborate with Commerce Operations, application development, infrastructure, and business teams to integrate AI solutions into existing workflows.
Requirements
- At least 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, including LangChain, LangGraph, AutoGen, CrewAI, OpenAI SDK, or Anthropic SDK.
- 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 Git, testing, debugging, code reviews, and CI/CD.
- Familiarity with A2A, Model Context Protocol, OpenAPI-based tool integration, multi-agent systems, human-in-the-loop workflows, and AI-agent guardrails is preferred.
- Experience with evaluation and observability tools such as LangSmith, Langfuse, tracing tools, evaluation harnesses, or AgentOps/LLMOps platforms is preferred.
- Knowledge of vector databases, semantic search, hybrid search, reranking, or knowledge-graph grounding is preferred.
- Familiarity with AI governance and safety practices, cloud platforms, MLOps or LLMOps, and commerce or supply-chain operations is preferred.
- Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field, or equivalent practical experience.
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.