Senior Forward Deployed Engineer

SecurityScorecard is hiring a Senior Forward Deployed Engineer to embed with our most strategic customers and turn raw security data into decisions executives act on. You’ll deploy onsite, learn the customer’s workflow, data, and decision logic firsthand, and build SecurityScorecard directly into how they already operate, closing gaps and creating new value instead of bolting on a generic integration.

We’re an AI product company at our core, so our FDEs build AI-first: using LLMs and modern AI tooling by default, and applying real data science to help customers quantify risk in terms finance already trusts.

What You’ll Do

• Deploy onsite with strategic customers to map their security, risk, and compliance workflows end to end, and find where value is leaking through manual effort or disconnected tools
• Gather requirements from practitioners and executives, and understand the dependencies across their people, process, and data before proposing a solution
• Weave SecurityScorecard into the customer’s existing data, logic, and process, rather than forcing them to adapt to a generic integration
• Build AI-native solutions by default: apply LLMs, ML models, and modern AI tooling to automate analysis and cut manual toil
• Run data analysis and data science work on customer and platform data, for example translating letter-grade ratings into financial terms like Annualized Loss Expectancy (ALE), Value at Risk (VaR), and ROI
• Design and deploy integrations, pipelines, and tools connecting SecurityScorecard to customer systems (SIEM, GRC, ticketing, data warehouses, and more)
• Architect and deploy solutions across AWS, Azure, and GCP environments to match each customer’s cloud footprint
• Prototype rapidly in the field, then harden solutions into supportable, production quality software
• Bridge Product, Engineering, and the customer, feeding field patterns back into the roadmap
• Own technical relationships with key accounts through renewal and expansion, alongside Customer Success and Sales Engineering
• Travel to customer sites for workshops, technical deep dives, and go-live support

Required Qualifications:

• 8+ years of software engineering experience, with significant time in a customer-facing, forward deployed, or solutions engineering capacity
• Hands-on experience building with AI, using LLMs, agentic frameworks, or ML models as core building blocks in shipped solutions
• A track record building AI-powered products or features, and a clear point of view on how AI changes forward deployed work
• Working data analysis / data science ability: comfortable turning raw data into a model a customer can act on (risk quantification, benchmarking, exposure modeling)
• Proven ability to ship production code independently in fast-moving, ambiguous, customer-facing environments
• Strong full stack fluency: backend services, APIs, scripting, data pipelines, and integration patterns (REST, webhooks, SSO/SAML, SIEM connectors)
• Solid architecture design experience across AWS, Azure, and GCP, and comfort designing solutions that fit a customer’s existing cloud environment
• Experience running discovery with enterprise stakeholders, from practitioners to executive sponsors, and scoping that into a technical solution
• Excellent communication skills, translating between technical detail and business or financial impact
• Bias toward action and comfort with ambiguity
• Prior experience in cybersecurity, GRC, or risk management is a strong plus
• Willingness to travel to customer sites (typically 20 to 40%, depending on account load)