AI Specialist

Overview

AI Specialist, KnoxAI

Job Title: AI Specialist

Department: Engineering / AI

Reports To: CTO

Location: New York City (Hybrid or Remote Considered)

Classification: Full-Time, Exempt

Estimated Compensation Range
: $180k-$200k

Focus: Co-own the development, training, and continuous evolution of KnoxAI to support Knox’s secure cloud and compliance mission

About Knox

Knox runs the largest Federal managed cloud, building and operating secure cloud and AI environments that support the U.S. government’s most critical missions — from national security and public safety to essential public services. Our customers rely on Knox to deploy production systems that meet the highest standards for security, reliability, and compliance.

Work at Knox is high-impact and purpose-driven. The problems we solve are high-stakes, the expectations are high, and the results are visible. Speed, rigor, and trust matter here - because the environments we secure cannot fail. Your contributions are visible, your expertise is relied upon, and the impact of your work is immediate and measurable. We operate at federal scale, securing some of the most sensitive government environments in the country - because the systems we build must perform without fail.

The AI Specialist will play a critical role in designing, building, training, and continuously improving KnoxAI, Knox’s proprietary AI capabilities that support secure cloud operations, compliance automation, and mission-critical decision-making.

This role is not limited to model training or experimentation. You will be responsible for shaping how KnoxAI evolves alongside the business, ensuring it is accurate, explainable, secure, and aligned with real customer and operational needs. You’ll work closely with Engineering, Product, Security, Compliance, and Operations to translate complex requirements into production-ready AI systems.

This is a hands-on, high-ownership role suited for an exceptional AI practitioner - someone who is both deeply technical and comfortable operating in ambiguous, high-stakes environments. Knox does not build novelty AI. We build AI that must work, scale, and stand up to scrutiny.

• Own the design, development, training, and ongoing refinement of KnoxAI models and systems, ensuring they meet evolving business, security, and compliance requirements

• Develop and maintain high-quality training pipelines, including dataset selection, labeling strategies, evaluation frameworks, and continuous feedback loops

• Improve model performance, reliability, explainability, and robustness through experimentation, tuning, and systematic evaluation

• Partner closely with Product and Engineering to translate real-world Knox use cases into production AI capabilities, not prototypes

• Collaborate with Security and Compliance teams to ensure AI systems align with federal requirements, audit-ability expectations, and risk management standards

• Implement monitoring and retraining strategies to detect drift, performance degradation, or emerging risks over time

• Contribute to architectural decisions around AI infrastructure, deployment, and MLOps in secure, regulated environments

• Document model behavior, assumptions, limitations, and decision logic to support internal understanding and external scrutiny

• Stay current on advances in AI, machine learning, and data science, selectively applying new techniques where they materially improve KnoxAI

• Remain hands-on while helping establish repeatable, scalable AI development practices as Knox grows

• Strong foundation in data science, machine learning, and applied AI, with demonstrated experience building and operating models used in real production systems

• Advanced proficiency in Python and modern ML / AI frameworks, with the ability to move comfortably between experimentation and production code

• Working proficiency in Node.js and/or Bun.js, with experience integrating AI and ML systems into production application backends and services

• Hands-on experience with data-centric AI practices, including dataset design, curation, labeling strategies, versioning, and managing data quality over time

• Proven ability to train,…