Point Wild

Point Wild helps customers monitor, manage, and protect against the risks associated with their identities and personal information in a digital world. Backed by WndrCo, Warburg Pincus and General Catalyst, Point Wild is dedicated to creating the world’s most comprehensive portfolio of industry-leading cybersecurity solutions. Our vision is to become THE go-to resource for every cyber protection need individuals may face - today and in the future.

Join us for the ride!

About the Role:

Point Wild is building the Trailblazer AI Team—a dedicated group focused on applying AI to enhance our products, drive business growth, and deliver real-world impact across multiple product lines (antivirus, VPN, identity protection, password management, and more).

As a Senior AI Engineer, you will play a critical role in building, deploying, and operationalizing machine learning models that drive innovation across the company. This role is hands-on, requiring expertise across the entire AI development lifecycle—from proof-of-concept experimentation to production-ready deployment. You will collaborate closely with R&D teams to scope AI initiatives, rapidly prototype models, and ensure scalable, maintainable AI solutions.

Day to Day:

• Develop and Deploy ML Models – Build and deploy machine learning models leveraging a possibly wide range of machine learning techniques (e.g., supervised/unsupervised learning, natural language processing, etc.).
• Rapid Prototyping & PoCs – Quickly build early-stage proof-of-concepts (PoCs) and conduct technical feasibility studies for AI initiatives.
• Full AI Lifecycle Ownership – Work across the entire ML pipeline, from prototyping in Python to deploying containerized models in AWS.
• Mentor & Collaborate – Work closely with other AI engineers, providing mentorship as needed and ensuring best practices in AI development.
• MLOps & Continuous Deployment – Partner with the Data/MLOps team to establish and maintain CI/CD pipelines for AI models.

Why this role matters?

• Core Execution Role – This person will be building actual AI models, directly impacting multiple product lines.
• AI at Scale – Ensuring that models are not just prototypes but can be deployed, scaled, and maintained in production environments.
• Speed & Innovation – Rapidly iterating and translating AI research into working solutions that drive business value.

What you bring to the table:

• Strong ML & AI Expertise – Deep experience in applied machine learning, including supervised, unsupervised learning, and NLP.
• Full-Stack AI Development – Comfortable building PoCs and deploying models in production (AWS, Docker, Kubernetes preferred).
• Proficient in Python & ML Frameworks – Strong coding ability with PyTorch, TensorFlow, or Scikit-learn.
• Product-Oriented Mindset – Able to align AI development with business impact and product goals.
• Startup Mentality – Comfortable operating in a fast-moving environment where rapid iteration and execution are key.
• Fluent English

Why Join Us?

• Work on Cutting-Edge AI – Build and deploy real-world AI solutions across multiple product lines.
• Be a Core Team Member – Directly shape the company’s AI strategy and impact millions of users.
• End-to-End AI Development – Own the full AI pipeline, from research and modeling to deployment and optimization.

Point Wild helps customers monitor, manage, and protect against the risks associated with their identities and personal information in a digital world. Backed by WndrCo, Warburg Pincus and General Catalyst, Point Wild is dedicated to creating the world’s most comprehensive portfolio of industry-leading cybersecurity solutions. Our vision is to become THE go-to resource for every cyber protection need individuals may face - today and in the future.

Join us for the ride!

About the Role:

We are seeking a hands-on Principal Architect to guide the creation and evolution of a cross-platform security SDK that will power our next generation of security products. This role goes beyond high-level architecture; you will actively shape the technical direction, provide concrete solutions, and ensure our SDK meets immediate product milestones while remaining flexible enough to incorporate additional capabilities as our product portfolio evolves.

As the architectural cornerstone of our team, you will collaborate with multiple stakeholders – product management, engineering, QA, and executive leadership – to integrate essential security functionalities into a cohesive, scalable, and performance-oriented SDK.
 

Day to Day:

• Own the End-to-End SDK Architecture:
  Define and maintain the overarching design and technical roadmap for a modular, cross-platform security SDK targeting Windows, macOS, and Android environments.
• Ensure Practical, Hands-On Implementation:
  Translate architectural concepts into actionable engineering tasks. Write proof-of-concept and production code where needed, review pull requests, and manage technical debt through sound design.
• Establish Core Frameworks & Integrations:
  Collaborate with developers to build foundational components (e.g., real-time scanning infrastructure, network filtering modules, system-level drivers). Guarantee these components are extensible to future functionalities (VPN, password management, etc.).
• Performance & Scalability:
  Drive performance optimization strategies, including resource usage, scan efficiency, and responsiveness, ensuring the SDK meets strict latency and overhead benchmarks.
• Security & Compliance:
  Implement and maintain industry-leading security practices in every layer of the SDK, covering kernel-level hooks and user-mode processes alike. This includes secure data handling and event logging.
• Cross-Functional Collaboration:
  Partner with product managers to align SDK capabilities with business objectives. Guide QA teams in designing test plans that validate performance, stability, and security requirements.
• Technical Leadership & Mentoring:
  Mentor senior and mid-level engineers on best practices, design patterns, and code review standards. Foster a culture of innovation, ownership, and continuous learning.

What you bring to the table:

• Extensive Experience in Software Architecture: 

  Proven track record (7+ years preferred) of architecting complex, system-level solutions—especially those involving security, endpoint protection, or driver development.

• Cross-Platform Expertise: 

  Deep understanding of Windows, macOS, and/or Android internals, including relevant APIs, driver frameworks, and security models.

• Hands-On Coding Skills: 

  Proficiency in C/C++ or similar low-level languages is critical; experience reviewing complex codebases and guiding teams on performance optimizations.

• Modular and Extensible Design: 

  Demonstrable success in creating flexible architectures that allow for adding or swapping modules without major refactoring.

• Performance & Scalability Mindset: 

  Familiarity with multi-threading, concurrency control, and the nuances of real-time security applications that demand minimal overhead.

• Strong Communication & Leadership: 

  Able to communicate architectural decisions clearly to both technical teams and non-technical stakeholders. Experience mentoring developers in high-performance environments.

• Fluent English

Preferred Qualifications:

• Knowledge of endpoint protection technologies (e.g., scanning engines, quarantine processes, or threat intelligence workflows) is critical.
• Experience with network security concepts such as packet filtering, VPN tunnels, or content inspection is highly desirable.
• Familiarity with cloud-driven architectures or distributed systems that interface with on-device security components.
• Past experience contributing to open-source security or system-level libraries.

Why Join Us?

• Professional Growth: Enhance your skills by collaborating closely with talented engineers and architects.
• Meaningful Impact: Help create software that protects millions of users from cybersecurity threats.
• Supportive Environment: Join a team dedicated to innovation, mentorship, and continuous learning.

Join us if you’re passionate about building next-generation security solutions, enjoy solving hard technical problems, and want to see your architectural vision come to life in real-world products. You’ll have the autonomy to make significant design decisions while staying actively involved in hands-on development.

Point Wild helps customers monitor, manage, and protect against the risks associated with their identities and personal information in a digital world. Backed by WndrCo, Warburg Pincus and General Catalyst, Point Wild is dedicated to creating the world’s most comprehensive portfolio of industry-leading cybersecurity solutions. Our vision is to become THE go-to resource for every cyber protection need individuals may face - today and in the future.

Join us for the ride!

About the Role:

Point Wild is building the Trailblazer AI Team—a dedicated group focused on applying AI to enhance our products, drive business growth, and deliver real-world impact across multiple product lines (antivirus, VPN, identity protection, password management, and more).

As an ML Ops / Data Engineer, you will play a critical role in standing up and maintaining the data pipelines and infrastructure that power AI initiatives across the company.

This role is a hybrid between data engineering and MLOps—ensuring that AI engineers have clean, structured data for modeling while also building and managing the ML infrastructure for deployment, scaling, and monitoring.

Day to Day:

• Data Pipeline Development – Design and maintain ETL/ELT pipelines to ingest, clean, and transform data from multiple product lines.
• AWS ML Infrastructure – Stand up and manage AWS-based ML infrastructure (e.g., S3 data lakes, AWS Glue, EMR, AWS Batch, Lambda, SageMaker).
• Model Deployment & MLOps – Own CI/CD for ML models, including environment setup, model versioning, containerization, and monitoring.
• Support AI Engineers – Ensure AI teams have reliable access to data, scalable training environments, and efficient deployment pipelines.
• PoC to Production Scaling – Help move AI proofs-of-concept from experimentation to fully productionized, scalable deployments.

Why this role matters?

• Enables AI at Scale – AI engineers are focused on modeling; we need dedicated expertise in data pipeline engineering and infrastructure.
• Critical to Operationalization – AI models are only valuable if they can be deployed, scaled, and monitored in production.
• Bridges Data & AI – This role ensures structured, clean, and usable data flows into AI initiatives while also handling model deployment.

What you bring to the table:

• Data Engineering Expertise – Experience building and maintaining ETL/ELT pipelines for large-scale data ingestion and transformation.
• Cloud & MLOps Proficiency – Strong knowledge of AWS services for ML infrastructure, model deployment, and automation.
• DevOps & CI/CD – Experience setting up CI/CD workflows for ML models, including versioning, monitoring, and automated retraining.
• Python & SQL Skills – Comfortable writing efficient Python and SQL scripts for data processing and model deployment.
• Practical, Execution-Oriented – Can balance quick PoC enablement with long-term scalability in AI deployments.

Why Join Us?

• Work on Cutting-Edge AI: Build and optimize real-world AI solutions across multiple security-focused product lines.
• Be a Key Player in AI Deployment: Own critical aspects of model development, productionization, and optimization.
• Learn & Grow in a High-Impact Team: Collaborate with top AI engineers and scale AI innovation within a growing company.