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This position was posted on May 16, 2026 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!
Job Overview
Location
Boston
Job Type
Full-time
Category
Software Engineering
Date Posted
May 16, 2026
Full Job Description
đź“‹ Description
- • Serve as the primary technical point of contact for prospects evaluating Lakera’s AI security platform, translating customer requirements into tailored solutions using Check Point’s AI Defense Plane.
- • Collaborate with Sales and Customer Success teams to guide prospects through the evaluation process and ensure seamless onboarding and adoption by customers.
- • Design and implement technical solutions aligned with enterprise customer infrastructure, addressing security, compliance, and IT governance requirements.
- • Support product configuration and deliver minor technical adjustments required for prospect and customer implementations to accelerate time-to-value.
- • Develop, maintain, and update technical documentation, playbooks, and implementation guides to standardize pre-sales and post-sales workflows.
- • Act as a bridge between customers and internal Product and Engineering teams by feeding real-world feedback into the product roadmap to drive platform evolution.
- • Build scalable Solutions Engineering practices by creating repeatable best practices, automation scripts, and documentation frameworks for team growth.
- • Conduct technical demonstrations, proof-of-concept deployments, and presentations to diverse audiences including technical teams, executives, and security stakeholders.
- • Engage with Fortune 500 companies, startups, and foundation model providers to secure AI stacks and mitigate adversarial misalignment risks.
- • Work closely with customers to understand their AI use cases and architect secure implementations that align with their existing cloud and DevOps environments.
- • Maintain expertise in hyperscaler platforms (AWS, GCP, Azure) and leverage tools such as Docker, Kubernetes, and Terraform to support deployment scalability.
- • Represent Lakera at industry events, conferences, and customer meetings to articulate the value of AI security and promote ethical AI adoption.
- • Stay current with emerging threats in AI systems and adapt solutions to address evolving adversarial tactics and compliance frameworks.
- • Operate with autonomy in a fast-paced startup environment, taking ownership of end-to-end customer technical engagements from discovery to delivery.
- • Advocate for customer needs internally while balancing organizational goals and product limitations to ensure realistic and impactful outcomes.
- • Contribute to the creation of Gandalf-related technical assets and educational materials to support community engagement and product awareness.
🎯 Requirements
- • 5+ years of experience as a Solutions Engineer, Sales Engineer, Solutions Architect, or similar role
- • Proficiency in Python and JavaScript ecosystems
- • Proven track record of enabling large-scale implementations on AWS, GCP, or Azure
- • Experience navigating enterprise security, compliance, and IT processes for B2B product deployments
- • Strong written and verbal communication skills with ability to present to technical and non-technical audiences
- • Comfort working in a fast-moving startup environment with high autonomy and ownership
🏖️ Benefits
- • Total on-target earnings (OTE) range of $160,000 to $200,000 based on experience and performance
- • Hybrid work model with office presence expected in Miami, Florida
- • Opportunity to shape the future of AI security at a company building the foundation for secure AI agents
- • Exposure to cutting-edge AI defense technologies and direct influence on product roadmap through customer feedback
Skills & Technologies
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About Lakera AG
Lakera AG provides AI security software that protects machine-learning applications from adversarial attacks, prompt injection, data poisoning and other emerging threats. The Swiss company offers a cloud platform that continuously monitors, detects and blocks malicious inputs in real time across large language models and computer-vision systems. Its technology plugs into existing ML pipelines via API and is used by Fortune 500 enterprises and AI-first startups to maintain model integrity, ensure compliance and reduce security risk without slowing deployment cycles.
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