Customer Success Engineer

About Bolster

Bolster turns the security paradigm upside down and removes threats and digital risks before an attack occurs. Our protection extends beyond the enterprise to customers and partners. Our approach is the antithesis of today’s cyber defense strategy, which is to wait for an attack than try and prevent it. Or worse, assume you have been breached and hope you can detect it. We leverage the power of AI to apply deep learning, computer vision, and natural language processing to identify criminal intent on millions of web pages daily. We tirelessly monitor the Internet to find malicious web pages that could cause harm and remove them. We empower companies to take back control of the Internet by continuously eliminating the threats that threaten their business, customers, and brand.

We are just getting started, and the future could not be more exciting. We’re growing the team in all functions as we transition from a small start-up into the next phase of our journey. We are looking for A-list talent who will have a meaningful impact, solve new challenges, and take ownership of the future of Bolster. If this is you, apply and join our team!

Qualifications

4+ years relevant work experience in Cybersecurity Engineering, Network or System Engineering, Architecture, technical support or consulting, professional services, or similar roles

Background in Internet and Security technologies such as Zero Trust, Threat Prevention, URL filtering, fraud detection, external threat monitoring, and other related subjects

Proven results working as a trusted technical advisor to drive value for customers, including the ability to interact with Security Teams, identify key customer stakeholders, engage and build relationships at various levels of technical and non-technical depth

Experience in managing multiple customers and projects in a dynamic environment with constant change to address emerging security risks and challenges

Demonstrated ability to prioritize work within a demanding environment, delivering consistent results even under pressure

Strong and effective verbal, written and interpersonal communication skills

CISSP Certification a plus

Responsibilities

Customer Success Engineers are product experts, technical advisors, and customer advocates

As the technical SME, you will work with Product, Engineering and Account teams to ensure our customers and partners get the most out of our products

Provide product-level technical expertise in feature adoption, product deployment, configuration optimization, and product advisories

Serve as a customer advocate driving product adoption

Identify innovative use cases to influence product roadmap and features

Gain an understanding of typical business challenges faced by our customers in order to appropriately map features in their security environments, as well as provide proactive information, guidance, and support

Ensure customers are maximizing their investment by rapidly implementing and operationalizing Bolster’s solutions to achieve their security objectives

Partner with account teams to deliver high-visibility, high-touch delivery strategy, technical account plan deployments, and product-level success plans

Travel: Open to occasional travel according to the need for strategic customer engagement and on-sites

Additional Information

Why Bolster

We are the leader in Anti-Phishing AI!

Bolster creates a Next-Generation Fraud Prevention SaaS platform & CheckPhish community platform based on pioneering work in Artificial Intelligence-based phishing and scam detection systems.

Bolster protects the world’s top brands like Zoom, Dropbox, Uber, LinkedIn, Roblox, and other Fortune 500 customers. We are funded by top-tier investors led by Thomvest Ventures and Crosslink Capital. Our team has over 100 years of combined cybersecurity experience at Cisco, Symantec, McAfee, Bell Labs, Open DNS, and Lacework.

Our AI/ML technology protects regular citizens from bad actors on the internet, using industry-leading deep learning, computer vision, natural language processing, and machine learning models for highly accurate real-time detection & automated takedown of fraudulent sites at the internet scale.

We also brought our technology to the community with CheckPhish,