AI Architect Business Applications

This role will be based in San Francisco CA NYC NY Bellevue WA or Chicago IL 

At LinkedIn we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option meaning you can both work from home and commute to a LinkedIn office depending on whats best for you and when it is important for your team to be together. 

The Tech & Analytics team builds the analytical and automation foundation that powers LinkedIns most important Go-to-Market decisions. We partner across Sales Customer Success Marketing and Engineering to create a unified understanding of GTM performance. Our mission is to transform data into proactive insights and intelligent systems that guide LinkedIns growth and efficiency. 

Were hiring an AI Architect to design build and launch AI-powered features inside the business applications our employees use every day. Youll work as a product-minded software builder turning LLMs agents and AI-driven automation into reliable well-scoped features that meaningfully improve how our internal teams get work done. 

This is a hands-on builder role. Youll own features end-to-end: from problem framing and prototyping through evaluation and rollout to monitoring in production. Youll partner closely with product managers data engineers and platform teams to ship AI capabilities that are ready to support an enterprise sales organization. 

Responsibilities: 

• Define the technical roadmap and architecture for Technology & Product Operations org including key decisions on frameworks tooling and practices. Partner with R&D to build applications leveraging our internal platforms as well as provide input to R&D on enhancements to our technical platforms and data infrastructure 
• Lead the hands-on design development and deployment of scalable data products AI/ML models (e.g. member friction customer impact anomaly detection) and GenAI-powered agentic workflows. 
• Serve as the subject matter expert on applying modern AI LLMs and ML techniques (e.g. RAG fine-tuning) to solve GTM business problems within Enterprise Applications in partnership with Operations Data Science and Engineering team 
• Design for quality and trust: define evaluation criteria build active monitoring implement safe use guardrails and continuously measure AI feature performance against business outcomes. 
• Mentor operations and analytics colleagues on AI tooling and applications setting a high bar for technical rigor code quality and engineering best practices through a lead-by-example approach. 
• Operate at scale and in production: instrument features to minimize latency and cost maximize reliability and accuracy; debug failure modes; iterate based on real usage. 
• Collaborate with Product Engineering and Data Science teams to operationalize and scale models from prototype to production ensuring reliability and measurable business impact. 
• Translate complex technical concepts and model outputs into clear concise and actionable narratives for non-technical stakeholders and senior leadership. 

Qualifications :

Basic Qualifications 

• Bachelors degree in Computer Science Engineering or a related field OR equivalent practical experience. 
• 5 years of professional software engineering experience building and maintaining production applications. 
• 5 years of experience building or contributing to enterprise or business applications (line-of-business tools internal platforms workflow systems or similar). 
• 1 years of experience with GenAI technologies and frameworks (e.g. LangChain LLM APIs). 
• 1 years of architecting building and deploying machine learning models and/or automated data solutions in production environments. 

Preferred Qualifications 

• Experience defining and applying AI evaluation strategies prompt engineering techniques and safety/guardrail patterns in real systems. 
• Strong knowledge of responsible AI practices: handling sensitive data access control PII abuse mitigation and human-in-the-loop patterns. 
• Experience with modern GenAI frameworks and tooling (e.g. LLM APIs orchestration frameworks agent frameworks vector stores RAG pipelines). 
• Experience operating software at scale  designing for reliability performance and cost in production. 
• Experience with observability evaluation and experimentation tooling for AI features (offline evals online A/B testing tracing feedback loops). 
• Comfort working across the stack as needed (backend services APIs and front-end integration) to deliver a complete user experience. 
• Strong product instincts: a sense for what makes an AI feature genuinely useful versus merely impressive. 
• Experience with enterprise business applications including Salesforce Tableau Gong and Pigment among others. 

Suggested Skills 

• Python 
• JavaScript 
• SQL 
• Machine Learning 
• Model Development & Deployment 

LinkedIn is committed to fair and equitable compensation practices. 

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $138000 - $225000. 

Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific work location. This may be different in other locations due to differences in the cost of labor. 

The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit  Information :

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.

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No

Employment Type :

Full-time