Senior Technical Lead for Autonomous Agentic Frameworks and System Integration

Software Engineering Technical Lead

Cisco's Customer Experience (CX) organization is one of the company's fastest-growing and most innovative teams, crafting a first-in-class digital experience for our customers and partners everywhere they connect with Cisco. CX Platform is a platform-centric to support the diverse requirements of the CX organization and is being built with emerging technologies including predictive AI and generative AI to drive additional customer success. We are at the epicenter of developing with modern, cloud-native technologies that allow us to stay agile and adaptable in a constantly evolving market. Pioneers in our field, CX enables customers to maximize value with a simple, unified Cisco experience, driving accelerated time to impact. We deliver on time with high quality & urgency, and we drive decisions with data and transparency while leading with ownership & accountability.
Your Impact
We are seeking a motivated and detail-oriented Software Engineering Technical Lead to join our growing Agent Harness Engineering team. In this role, you will not only help build persistent, goal-oriented agent systems that "think" and "act" autonomously but also lead the strategic planning and execution of the agentic roadmap. You will bridge the gap between technical innovation and project delivery, ensuring that our autonomous systems are built on time, align with cross-functional milestones, and integrate seamlessly into the broader ecosystem.
Key responsibilities include designing, building, and deploying autonomous agents that operate within dynamic environments, making independent decisions to achieve goals. You will lead the end-to-end lifecycle of agentic projects, defining project scopes, breaking down complex technical requirements into actionable tasks, and managing the team's backlog to ensure high-velocity delivery. Implementing multi-agent, collaborative systems and designing complex agent workflows using frameworks like LangGraph, AutoGen, or CrewAI will be part of your role. You will act as the primary technical point of contact to coordinate schedules and dependencies across multiple teams, ensuring that agentic capabilities are synchronized with organizational priorities. Developing and integrating tools, APIs, and databases for agents to interact with, enabling real-world actions, is essential. You will optimize large language model (LLM) interactions, including prompting, fine-tuning, and context management to enhance reasoning and reduce hallucinations. Providing regular status updates and risk assessments to leadership regarding project timelines and technical blockers is expected. Additionally, you will collaborate with engineering teams to integrate autonomous capabilities into existing software development life cycles (SDLC), championing Agile methodologies and best practices for task tracking and documentation.
Minimum Qualifications:
Bachelors + 8 years of related experience OR Masters + 6 years of related experience.
Experience in designing, developing, and deploying AI agents, agentic systems and/or agentic orchestration patterns.
Experience with evals driven development and observability for non-deterministic systems.
Experience developing code in Python.
Experience with frameworks such as LangChain or LangGraph.
Experience with cloud-based data platforms like SnowFlake.
Experience with asynchronous programming (multi-turn agents or multi-step agents or similar).
MCP or tool-integration patterns for enterprise systems.
Experience using Jira and GitHub.
Preferred Qualifications:
Demonstrated leadership skills with the ability to collaborate across teams.
Ability to lead projects, organize and manage deliverables.
Experience working through new features and prioritizing execution.
Strong communication skills with both technical and non-technical stakeholders.
Proactive "Go Getters" comfortable in fast-paced environments.
Experience building applications with frontier models and open-source LLM Ecosystems.
Strong understanding of large language models (LLMs), including how they work and how to train and focus them on specific areas.
Experience with natural language processing and prompt engineering.
Experience with enterprise security and agentic access control patterns.
Experience with using AI Development Tools like Claude Code, Codex, Snowflake Cortex or similar.