The application window is expected to close on: 04/04/2026Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

Position Overview:

We are seeking a skilled AI Engineer to design, deploy, and scale Large Language Models (LLMs) and advanced AI frameworks such as LangChain and LangGraph. The ideal candidate will have expertise in building and managing knowledge databases, implementing Retrieval-Augmented Querying (RAQ), and fine-tuning LLMs to optimize performance and relevance. This role involves working with vector databases, multi-agent systems, and ensuring efficient data ingestion, retrieval, and response synthesis in AI applications.

Key Responsibilities:

• Deploy and manage Large Language Models (LLMs) at scale, integrating function-calling capabilities to enhance query handling and context awareness.
• Develop and maintain knowledge databases, including vector and graph databases, to support retrieval-augmented generation (RAG) workflows.
• Implement Retrieval-Augmented Querying (RAQ) techniques to optimize data retrieval and response accuracy.
• Fine-tune LLMs using techniques such as prompt engineering and model tuning to improve output quality and reduce hallucinations.
• Design and build multi-agent AI systems using frameworks like LangChain and LangGraph for complex, stateful workflows and enterprise-grade solutions.
• Manage conversational memory and context windows, including short-term and long-term memory strategies for AI agents.
• Collaborate with cross-functional teams to integrate AI solutions with existing infrastructure and ensure compliance with responsible AI policies.
• Monitor and optimize AI system performance, including embedding creation, vector search efficiency, and LLM inference latency.
• Implement human-in-the-loop augmentations and guardrails to maintain AI safety and reliability.

Required Skills and Experience:

• Strong experience with Large Language Models (LLMs) and foundational AI frameworks such as LangChain and LangGraph.
• Proficiency in building and managing vector databases (e.g., ChromaDB, Pinecone, Weaviate) and graph databases (e.g., Neo4j).
• Expertise in Retrieval-Augmented Generation (RAG) and query embedding techniques.
• Hands-on experience with LLM fine-tuning, prompt engineering, and embedding model creation.
• Familiarity with multi-agent AI architectures and orchestration protocols (e.g., Agent-to-Agent communication, Model Context Protocol).
• Knowledge of AI memory management concepts including semantic, episodic, and procedural memory.
• Programming skills in Python and familiarity with AI SDKs and APIs.
• Understanding of responsible AI principles, data privacy, and security considerations in AI deployments.
• Experience with monitoring tools for LLMs and AI applications (e.g., Python Agent for telemetry).

Minimum Qualifications:

• Bachelors + 8 years of related experience, or Masters + 6 years of related experience, or PhD + 3 years of related 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.

Message to applicants applying to work in the U.S. and/or Canada:

The starting salary range posted for this position is $157,600.00 to $199,600.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units,