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Forward Deployed Engineer

AI Summary
The Forward Deployed Engineer owns technical customer onboarding and deployment of the SAFE cyber-risk platform across the Americas. The role combines customer-facing implementation, API integration, Python scripting, workflow automation, troubleshooting, and escalation management. This engineer bridges enterprise customers with product and engineering teams, translating business outcomes into reliable technical solutions. The position requires frequent independent problem solving, effective use of AI tooling, and the ability to travel to customer sites when needed. It is a high-intensity role supporting complex enterprise security environments.
Remote from
USA, Canada, LATAM
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
13 Dec 2026
Listing views
26
Application actions
2
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Opportunity details

About this role.

Most boards and executives are currently flying blind when it comes to cyber risk. They are guessing. At Safe, we’ve built an AI-driven engine that finally gives the C-Suite a clear, quantified, and real-time view of their security posture. We don’t just provide data; we provide certainty.

We are a $170M Series C-funded category leader. We don’t play in the mid-market; we operate at the highest levels of global enterprise. Today, we are proud to serve 10% of the Fortune 500, protecting global icons such as Apple, Netflix, AT&T, Verizon, and Victoria’s Secret.

As we scale toward our next chapter, we are looking for high-performers who want to do the best work of their careers at the intersection of AI and Cybersecurity.

The Culture Memo: Our Operating System

Safe is not a typical corporate environment. We are a high-intensity, mission-driven team. We value builders who want to define a category and work alongside people who are equally committed to excellence.

  • Extreme Ownership: We don’t do “not my job.” We hire people who see a gap and own the solution from start to finish.

  • The Elite Standard: We serve the most sophisticated companies on the planet. Our work must be bulletproof. Whether it’s a line of code or a sales deck, we aim for Tier-1 quality every time.

  • Methodology & Rigor: We don’t wing it. From Force Management and MEDDICC in sales to data-driven sprints in engineering, we rely on proven frameworks to stay disciplined and predictable.

  • Radical Candor: We move too fast for politics or sugar-coating. We value direct, honest feedback that helps us find the right answer quickly.

  • The Series C Hustle: We have the stability of a well-funded leader but the heart of a startup.

The Perks & Ownership:

We want our team to feel like owners because they are owners. We trust our people to manage their results and their time.

  • Meaningful Equity: Every “Safestar” is a shareholder. You aren’t just an employee; you are a partner in our success.

  • Unlimited Leaves: We don’t believe in clock-watching. We offer unlimited leave because we trust you to take the time you need to recharge while staying committed to the mission.

  • Comprehensive Benefits: We provide top-tier medical insurance and wellness benefits to ensure you and your family are well cared for.

  • Career Trajectory: We are growing aggressively. For high-performers, the path for advancement moves at the speed of your ambition.

As a Forward Deployed Engineer, you are the implementation owner of a customer’s success with SAFE, from the first onboarding call to a working, trusted deployment delivering value as a key part of their business processes. You sit between the customer’s implementation teams and SAFE’s engineering teams, understanding all sides well enough to translate between them. You have detailed product knowledge to be able to implement customers’ business needs using existing features, and create customisations as needed.

In this role you will have a strong understanding of SAFE/Industry best practice, guiding the customer to achieve their outcomes on the SAFE Platform, This will include educating and enabling the customer, as well as a technical implementation.

You build the scripts, configure the platform, integrations, agents and automations that get a customer live. You diagnose what stands in the way of a customer’s success, and where necessary engage internal teams with a clear, evidenced problem statement with an agreed outcome. You hold the end-to-end picture of how SAFE works, so a conversation between a customer and SAFE teams reaches a decision quickly.

You use AI tooling every day to engage with customers more effectively, work with more autonomy and enable others, improving existing processes and tooling to achieve rapid deployments and value realisation.

What you’ll do:

Own customer onboarding and delivery

  • Lead technical onboarding for assigned customers: scope, plan, configure, integrate and confirm the customer is getting value.

  • Own each engagement to a defined outcome. Keep the customer and internal teams informed on progress, risks and next steps.

  • Travel to customer sites for workshops, deployments and escalations.

  • Write scripts and lightweight automations that speed up onboarding, data loading, integration set-up and repeat tasks.

Technical implementation

  • Collect technical details from customers about their environment, data sources and integrations: authentication, permissions, network constraints, payload formats and expected behaviour.

  • Configure and customise the SAFE platform to meet customer business needs, making direct product fixes where appropriate.

  • Build and test customer-specific workflows and AI agents, using SAFE and third-party APIs as needed.

  • Build custom solutions to achieve customer outcomes where product gaps exist.

  • Create tooling to accelerate delivery processes and automate repetitive tasks.

  • Diagnose failed or incomplete integrations and data flows.

Debug and troubleshoot

  • Reproduce and investigate issues using logs, platform telemetry and platform knowledge. Work methodically from symptom to evidence to cause, with or without AI tooling

  • Present each issue to engineering with the evidence: what happens, what should happen, who it affects, and what you have already ruled out.

  • Stay with the issue until the customer has a resolution or an agreed workaround.

Bridge the customer and engineering

  • Talk to engineering stakeholders as a peer. Define the outcome a customer needs, not the implementation.

  • Join customer and internal technical calls to provide expert guidance and drive project deliverables to completion.

  • Spot patterns across customers. Raise them as product feedback with the customer’s business outcome and their own words.

  • Act as an internal customer, working closely with Product teams to ensure that new features are understood and have a clear route to deliver customer value.

Use AI tooling to scale your work

  • Use AI tools to analyse logs, draft scripts, summarise issues and prepare customer-facing material, using your experience to refine outcomes.

  • Turn repeated tasks into reusable scripts, AI skills or automations that the wider team can use.

What you’ll bring:

Essential

  • Ownership and accountability. You take a problem as yours until it is closed, and you say so early when something slips.

  • Creative thinking and problem-solving. You find a route to success, resolving issues as you hit them.

  • Curiosity. Not everything is documented. You explore, discover and experiment to achieve an outcome.

  • Experience in script building, product delivery and working directly with customers. This can come from a customer-facing technical role or substantial project work.

  • Product onboarding experience. You have taken customers or users from set-up to live use of a technical product.

  • API fluency. You can read API documentation, call and chain endpoints, handle authentication, and interpret responses and errors.

  • Debugging and troubleshooting skills. You work methodically from symptom to evidence to cause, respecting customer data handling requirements.

  • Excellent written/verbal communication. You explain technical findings and concepts clearly to the level of the target audience, backed by an expert understanding of the system architecture.

  • Development. You write scripts that call APIs, process data, and automate customer tasks using Python as a preferred language. You understand code generated by AI tools for human review and challenge.

  • Cloud Services. You understand core cloud-based services and how they can be implemented at customers and used by SAFE.

  • Demonstrable use of AI tooling. You can show real examples of using AI to troubleshoot, script or automate, and you can say where it fell short.

  • Ability to travel to customer sites.

Nice to have

  • Exposure to cybersecurity, risk management or security-tool integrations (for example, vulnerability scanners, SIEM, asset inventories or identity providers).

  • Bash or PowerShell.

  • Experience in a customer-facing technical role (forward deployed, solutions, customer or support engineering) at a SaaS or enterprise software company.

  • Experience working in distributed, multi-time-zone teams.

Why this role is exciting:

  • Own customer outcomes at the point where SAFE meets real enterprise environments.

  • Work with engineering, product and customer teams on problems that shape the platform.

  • Build creative solutions to problems, both customer facing and internal

  • Learn cyber risk, Third Party Risk Management (TPRM) and Continuous Threat Exposure Management (CTEM), a growing part of cybersecurity.

  • Use Python, APIs and AI tooling to remove manual work for yourself and the team.

Compensation

Additional Information

If you’re passionate about cyber risk, thrive in a fast-paced environment, and want to be part of a team that’s redefining security, we want to hear from you! 🚀

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a demanding customer-facing engineering role involving enterprise integrations, production troubleshooting, custom automation, and accountability for end-to-end delivery outcomes. The engineer must rapidly diagnose ambiguous issues while coordinating customers, product teams, and engineering stakeholders.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$172,500
US market range (per year)$140k–$210k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. The annual cadence is inferred from the full-time senior technical implementation scope and standard professional compensation conventions in the Americas. Estimated annual market compensation for a Forward Deployed Engineer with enterprise SaaS, Python, API, and cybersecurity exposure is USD 140,000 to USD 210,000, with an estimated midpoint of USD 172,500.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you approach onboarding an enterprise customer with several security-data integrations?

I would begin by defining the customer’s intended business outcomes, stakeholders, success criteria, and delivery milestones. I would then inventory systems, authentication methods, permissions, network constraints, payload formats, and data-quality requirements before building an integration plan. I would validate each connection incrementally, document evidence and risks, and keep the customer informed through regular progress updates.

Describe how you would diagnose a failed API integration.

I would reproduce the failure, inspect request and response data, validate authentication and authorization, and compare the implementation with the API documentation. I would use logs and telemetry to isolate whether the issue is caused by configuration, network access, payload structure, rate limits, or platform behavior. If escalation were required, I would provide engineering with a concise evidence package, expected versus actual behavior, impact, and completed investigation steps.

How do you use AI tools responsibly when writing scripts or investigating customer issues?

I use AI tools to accelerate log analysis, draft automation ideas, summarize investigation findings, and generate starting points for scripts. I validate all generated code and conclusions through documentation, testing, security review, and my own technical judgment. I also avoid exposing sensitive customer data to tools that are not approved for that use.

How would you communicate a product gap to an internal engineering team?

I would frame the issue around the customer’s business outcome rather than prescribing a solution immediately. I would include the affected workflow, severity, customer impact, reproducible evidence, current workaround, and the desired result. This gives engineering enough context to assess scope and prioritize an effective solution.

What makes a reusable onboarding automation successful?

A successful automation solves a repeated, measurable delivery problem while remaining secure, observable, and easy for others to use. I would design it with clear inputs, error handling, documentation, and validation steps, then test it against realistic customer scenarios. I would measure its impact through reduced setup time, fewer errors, and improved consistency across deployments.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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