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AIArchitectBusinessApplications
“AI Architect - Business Applications at LinkedIn. Skills: AI Architecture, GenAI, Machine Learning, Business Applications. Define technical roadmap and architecture. Build applications leveraging internal platforms”
What You'll Achieve.
Improve how internal teams get work done; Support an enterprise sales organization; Ensure reliability and measurable business impact
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Bachelor's degree in Computer Science or equivalent practical experience, 5+ years software engineering experience, 5+ years building business applications, 1+ years GenAI technologies and frameworks, 1+ years architecting ML models or data solutions
Nice to Have
Experience defining AI evaluation strategies, Experience with prompt engineering techniques, Experience with safety/guardrail patterns, Knowledge of responsible AI practices, Experience with modern GenAI frameworks and tooling, Experience operating software at scale, Experience with observability, evaluation, and experimentation tooling for AI features, Comfort working across the stack, Product instincts, Experience with enterprise business applications
What You'll Do.
Define technical roadmap and architecture
Build applications leveraging internal platforms
Provide input to R&D on enhancements
and deployment of data products
Lead development of AI/ML models
Lead development of GenAI-powered agentic workflows
Serve as subject matter expert on AI
Apply AI techniques to solve GTM business problems
Design for quality and trust
Define evaluation criteria
Build active monitoring
Implement safe use guardrails
Continuously measure AI feature performance
Mentor colleagues on AI tooling and applications
Set high bar for technical rigor
Set high bar for code quality
Set high bar for engineering best practices
Operate at scale and in production
Instrument features to minimize latency and cost
Instrument features to maximize reliability
Instrument features to debug failure
Iterate based on real usage
Collaborate to operationalize and scale models
Ensure reliability and measurable business impact
Translate complex technical concepts
Translate model outputs
Create actionable narratives for non-technical stakeholders
How You'll Work.
Team & Collaboration
Partner with product managers; Partner with data engineers; Partner with platform teams; Partner with Operations; Partner with Data Science; Collaborate with Product; Collaborate with Engineering; Collaborate with Data Science teams
Communication Scope
Clear narratives; Concise narratives; Actionable narratives
Process & Methodology
Problem framing, Prototyping, Evaluation, Rollout, Monitoring
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