Senior Staff AI Engineer - Enterprise AI (Agentic AI)

Location:

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

This role will be based in Sunnyvale, CA. 

Team Overview: 

LinkedIn’s Enterprise AI team creates meaningful impact by connecting individuals to opportunities! The team works on a wide range of technical solutions including LLM fine-tuning, content generation, LLM-as-a-judge, prompt engineering, embedding-based retrieval, and search/ranking.

The team has an ambitious roadmap and partners closely with Core AI (Foundational AI), Product, and other teams to deliver scalable, modern AI solutions with global member impact. The key focus is our agentic Hiring Assistant or LiHA product which is one of the top products for LinkedIn in 2026. 

If you’re looking to lead a highly visible, fast-moving, and exceptionally talented team at the intersection of cutting-edge innovation and real-world impact—and have fun while doing it— Enterprise AI is the place for you!

Responsibilities:

Provide expert thought leadership, technical guidance, and direct contribution for a team of 15-25 engineers working on high-impact initiatives for one of LinkedIn's top products. 

• Lead the design of conversational and agentic AI systems that perform functions related to talent acquisition.

• Build and scale production-grade LLM agents that collect structured candidate signals, answer questions, and orchestrate multi-step, tool-using workflows with memory and reasoning.

• Develop automated screening and interview agents to accelerate qualification, improve signal quality, and reduce time-to-interview while ensuring fairness and compliance.

• Define technical direction and impact metrics, connecting conversational quality to downstream hiring outcomes and leading experimentation in enterprise-scale environments.

• Evaluate and drive key engineering decisions such as whether to fine tune models or leverage off the shelf, how to best implement RAG, etc.  

• Collaborate with many talented AI Engineers, leaders, and cross-functional partners

• Contribute to solutions as an expert technical practitioner 

Basic Qualifications:

• Bachelor’s degree in Computer Science or related technical field or equivalent technical experience
   
• 7+ years of industry experience with large-scale recommendation systems

Preferred Qualifications:

• 4+ years of technical leadership (Staff+) experience, including recent experience at the Senior Staff / L7 / Principal Engineer level. \

• MS or Ph.D. in Computer Science or related technical discipline

• Experience designing agentic architecture, framework, and/or orchestration systems. 

• Strong understanding of reinforcement learning (RL) techniques and their application to agent training in language-based environments.

• Experience with specific techniques for improving LLM post-training: e.g., program synthesis, symbolic reasoning, or neuro-symbolic AI.

Suggested Skills:

• AI Modeling
• Reinforcement Learning (RL)
• Technical Leadership
• Large Language Models (LLMs)
   

You will Benefit from our Culture:

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

Compensation:

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $191,000 - $315,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For additional information, visit: https://careers.linkedin.com/benefits.

Equal Opportunity Statement 

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

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Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

• Documents in alternate formats or read aloud to you
• Having interviews in an accessible location
• Being accompanied by a service dog
• Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

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Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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