Applied AI Engineer

Pure Storage

Location not specified

Full Time

Posted May 6, 2026

$172k - $258k

Not Specified

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Job Description

This role involves providing technical advisory and strategic guidance on AI and machine learning deployment for enterprise clients, combining scientific expertise with business acumen to shape AI strategies, lead technical engagements, and contribute to research and thought leadership in the AI industry.

Key Responsibilities

Lead technical discovery and advisory engagements with customers to identify high-value AI use cases.
Advise on AI deployment models, training strategies, inference optimization, data pipeline design, and safety frameworks.
Collaborate cross-functionally to qualify and position AI opportunities and develop proof-of-value prototypes.
Create AI enablement content such as technical walkthroughs, qualification guides, workshops, and use case frameworks.
Present at industry conferences, publish technical content, and represent the company in strategic technology partnerships.
Operate autonomously to scope and drive high-impact AI initiatives to completion.

Requirements

An advanced degree in a quantitative field such as Computer Science, Physics, Mathematics, Engineering, or an equivalent demonstrated through publications and production system experience.
At least 8 years of experience building and deploying AI/ML systems in cloud or on-premises environments.
Deep expertise in modern AI/ML large language models, distributed training, inference optimization, agentic systems, evaluation alignment frameworks, and classical ML.
Fluency with the modern AI stack including PyTorch, vLLM, Ray, Kubernetes, and data platforms such as Spark, Snowflake, Kafka.
Ability to scope and carry out research projects that support critical business objectives, both independently and collaboratively.
Excellent written, verbal, and presentation skills, with the ability to communicate clearly with hands-on data scientists and C-suite decision-makers.
Experience with large-scale AI infrastructure including GPU clusters and high-performance storage.
Experience in customer-facing technical advisory or consulting roles with enterprise accounts.
Experience leading independent, multi-year research from concept to publication or large-scale production deployment.
Exposure to multiple industry verticals such as financial services, healthcare, telecommunications, or manufacturing.
Publication record, conference presentations, or recognized technical presence.
Background combining applied research with shipping production systems.
Familiarity with CRM opportunity management systems such as Salesforce.