AI Engineet

JD:

Cisco has opened a new AI position and the requirement is immediate. We need to submit strong and relevant profiles at the earliest. Please prioritize this request and start sharing suitable resumes as soon as possible. The client expects quick action on this, so timely submission is critical.

Key Responsibilities

· Research and prototype Advanced RAG techniques (e.g., chunking strategies, retrieval optimization, knowledge graph integration).

· Explore and implement Agentic AI patterns (e.g., supervisor vs plan-execute workflows).

· Investigate and develop methods for reducing memory footprint and improving LLM response quality.

· Design and experiment with LLM fine-tuning strategies for domain-specific applications.

· Collaborate on data preprocessing pipelines , including SQL-based processing and advanced text preprocessing techniques.

· Leverage LangChain ecosystem tools : LangChain, LangGraph, LangSmith for building and evaluating AI workflows.

· Experiment with LLMs such as GPT-4+, Gemini, LLaMA, and others for various use cases.

· Apply design patterns in AI and backend development for scalability and maintainability.

· Contribute to ML Ops and LLM Ops best practices to streamline research-to-production pipelines.

Must-Have Skills & Experience

· Programming: Deep expertise in Python, asynchronous programming, and software design patterns.

· Data Processing: Strong SQL skills, data preprocessing, and transformation techniques.

· LangChain Ecosystem: Hands-on experience with LangChain, LangGraph, and LangSmith.

· LLM Experience: Familiarity with leading models like GPT-4+, Gemini, LLaMA.

· AI Expertise:

o Agentic AI patterns.

o Advanced RAG methods.

o LLM fine-tuning approaches.

o ML Ops & LLM Ops workflows.

Nice-to-Have Skills

· Cloud Platforms: AWS or GCP experience.

· DevOps: CI/CD and containerized environment familiarity