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AI Architect - SaaS GTM Tech & Analytics | IC4

Sunnyvale, USA

Full-time

Mid · 5+ years experience

Hybrid

Discovered 5 days ago

javascriptlangchainpythonsql

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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.

Basic Qualifications

Bachelor's 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.
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 Dynamics, Microsoft Fabric, and Gong among others.
Python
JavaScript
SQL
Machine Learning
Model Development & Deployment

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 Dynamics, Microsoft Fabric, and Gong among others.
Suggested Skills
Python
JavaScript
SQL
Machine Learning
Model Development & Deployment
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $141,000 to $231,000.
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 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.
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AI Architect - SaaS GTM Tech & Analytics | IC4

Key Skills for This Role

Full Job Posting

Responsibilities

Basic Qualifications

Preferred Qualifications

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