Asks for

The ad says“Expertise in Agentic AI with hands-on experience in AI Agent development, including designing, orchestrating, and deploying autonomous systems and multi-agent workflows.”
The ad says“Expertise in Agentic AI with hands-on experience in AI Agent development, including designing, orchestrating, and deploying autonomous systems and multi-agent workflows.”
The ad says“Broad perspective and ability to articulate architectural design choices regarding GPU compute scaling, model latency, and AI routing, including knowledge of AI API gateways and proxying solutions like Apache APISIX or LiteLLM.”
The ad says“Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.”
The ad says“Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.”
The ad says“Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.”
The ad says“Experience developing robust APIs using popular frameworks such as FastAPI, Flask, Spring Boot or similar.”
The ad says“Experience developing robust APIs using popular frameworks such as FastAPI, Flask, Spring Boot or similar.”
The ad says“Experience in Python and/or Java/J2EE.”
The ad says“Experience in Python and/or Java/J2EE.”
The ad says“Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.”
The ad says“Broad perspective and ability to articulate architectural design choices regarding GPU compute scaling, model latency, and AI routing, including knowledge of AI API gateways and proxying solutions like Apache APISIX or LiteLLM.”
The ad says“Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.”
The ad says“Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.”
The ad says“Experience in Python and/or Java/J2EE.”
The ad says“Experience developing robust APIs using popular frameworks such as FastAPI, Flask, Spring Boot or similar.”
The ad says“Experience contributing to threat modeling, specifically identifying and mitigating risks regarding prompt injection or AI data leakage.”
The ad says“Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.”

The application window is expected to close on: 10/30/2026

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

Meet the Team

The team operates at the cutting edge of AI, functioning within the broader Customer Experience Engineering organization as a specialized Customer Reliability Engineering (XRE) group to support Cisco’s customer experience (CX) platform. Our primary mission is to ensure seamless, highly reliable production systems by fiercely resolving complex customer reliability issues, managing critical escalations, and ensuring AI-driven solutions are secure and performant. We are a collaborative, agile group of MLOps experts, reliability engineers, and software developers who thrive on troubleshooting and stabilizing complex technical ecosystems. Working closely with design, data science, and product management, our efforts directly protect Cisco's CX product roadmap and ensure long-term customer success. What’s most exciting is the opportunity to shape the reliability of a rapidly evolving AI landscape, directly impacting the customer experience by tackling complex challenges in hybrid cloud environments, LLM orchestration, and inference optimization every day.

Your Impact

As an AI Operations Engineering Technical Leader focusing on Agentic AI and MLOps, you will drive the operationalization of complex autonomous agent architectures into secure, scalable, and high-performing production environments. Define and establish robust MLOps practices, foundational ML pipelines, and model serving architectures to bring innovative Agentic AI concepts out of the lab and into customer-facing products. Design and implement robust telemetry monitoring tools to track token usage, control compute costs, monitor agent reasoning paths, and ensure optimal model performance and security. Proactively resolve complex infrastructure challenges by managing containerized models on GPU clusters and addressing model inference issues. Guide architectural choices based on deep market knowledge and mentor peers, ensuring our Agentic AI platforms remain reliable, scalable, and ahead of the curve.

Minimum Qualifications

Bachelors degree and 8+ years of related experience, or Masters and 6+ years of related experience.
Experience within Software Engineering and DevOps job families, specifically focusing on building scalable infrastructure.
Experience operationalizing Large Language Models such as OpenAI, Anthropic, Llama or similar and utilizing LLM frameworks such as LangChain or LangSmith.
Experience in Python and/or Java/J2EE.
Experience developing robust APIs using popular frameworks such as FastAPI, Flask, Spring Boot or similar.
Experience with CI/CD concepts for machine learning and familiarity with model tracking and MLOps frameworks such as ClearML, MLflow, Weights & Biases or similar and containerization utilizing Docker and Kubernetes.

Preferred Qualifications

Expertise in Agentic AI with hands-on experience in AI Agent development, including designing, orchestrating, and deploying autonomous systems and multi-agent workflows.
Broad perspective and ability to articulate architectural design choices regarding GPU compute scaling, model latency, and AI routing, including knowledge of AI API gateways and proxying solutions like Apache APISIX or LiteLLM.
Strong verbal and written communication skills to effectively negotiate delivery trade-offs (e.g., latency vs. model accuracy vs. cost) with cross-functional partners.
Experience contributing to threat modeling, specifically identifying and mitigating risks regarding prompt injection or AI data leakage.
Proven leadership ability to facilitate knowledge-sharing sessions, lead postmortems, and mentor junior team members on technical designs.

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 $216,300.00 to $280,800.00 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, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:

10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
Additional paid time away may be requested to deal with critical or emergency issues for family members
Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

.75% of incentive target for each 1% of revenue attainment up to 50% of quota;
1.5% of incentive target for each 1% of attainment between 50% and 75%;
1% of incentive target for each 1% of attainment between 75% and 100%; and
Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area:

$216,300.00 - $322,900.00

Non-Metro New York state & Washington state:

$197,500.00 - $287,300.00

* For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.

** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.