Solutions Engineer (Miami, Florida)

Lakera AG

Job Overview

Location

Boston

Job Type

Full-time

Full Job Description

📋 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

Python

JavaScript

AWS

Azure

GCP

Hybrid

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Lakera AG

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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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