Forward Deployed Engineer

DigiCert

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Location: United States
Job Type: full-time
Work Format: 🌍 Remote
Salary: $155,000 - $200,000 USD
Posted: November 7, 2026

Job Description

Who we are

DigiCert is a global leader in intelligent trust. We protect the digital world by ensuring the security, privacy, and authenticity of every interaction. Our AI-powered DigiCert ONE platform unifies PKI, DNS, and certificate lifecycle management, to secure infrastructure, software, devices, messages, AI content and agents. Learn why more than 100,000 organizations, including 90% of the Fortune 500, choose DigiCert to stop today’s threats and prepare for a quantum-safe future at

Job summary

Forward Deployed Engineers at DigiCert are software engineers who embed with a business function (Sales, Support, Finance, Legal, HR, Procurement, Marketing), learn how the work actually gets done, and ship production AI solutions that drive measurable efficiency and ROI : agents on our systems of record, automated workflows, and AI-native tools wired into the architecture people already use.

You are the hands-on CTO of each engagement. You’ll find where AI deliver s the highest return , decide the technical plan, write and deploy the code, and keep improving it after launch.

This is not a research role. You will own the work from first conversation to production, and are judged on what ships and what it returns, not on pilots or demos.

What you will do

Embed and find the work. Sit with business users, understand and map their workflows, data, and systems, and find where AI accelerates growth or saves the most time and money.
Own the architecture. Decide whether to build, buy, or configure solutions, weighing cost, speed, and long-term fit, and lead the technical side of vendor evaluations.
Write and ship production code. Build integrations, agents, and workflows with retrieval, tool use, and human-in-the-loop review. Test, deploy, and support what you ship.
Make AI reliable. Build systems that hold up against fragmented data and unpredictable model behavior. Find the failure cases before users do and decide where humans stay in control.
Build the shared foundation. Partner with IT, Security, and Engineering on model access, identity and permissions, data connectivity, observability, and evaluation. Turn one-off wins into reusable components , so each engagement ships faster than the last.
Prove the value. Every solution ships with a baseline, a measured improvement, and a hard number (hours saved, cost avoided, cycle time cut) for the sponsoring executive.
Leave the business stronger. Work with our enablement team to train operators and power users, so systems keep running and improving after you move on.

How we work

The Enterprise AI team is intense by design. It's a small team with an outsized impact on the business: what we ship changes how DigiCert runs, and the results reach the top of the company. The pace is fast and the standards are high, but so is the support. People share what they learn, challenge each other, and step in to help .

This is probably not the right place if you want a narrow scope, a predictable pace, or distance from internal customers. This role is built for engineers who want ownership , hard problems, a steep learning curve, and work that visibly moves the business.

What you will have

4+ years building and shipping production software that people depended on, and supporting it after launch. Software engineering, forward-deployed engineering, solutions engineering, or startup backgrounds all fit.
2+ years building with LLMs in production: agents, retrieval, tool calling (including MCP), and context engineering. You can explain how you measured and improved a system’s performance, and what it was worth to the business.
Strong coding ability in Python or TypeScript/JavaScript. You write, test, review, and deploy your own code, and you are fluent with APIs, webhooks, data pipelines, and authentication (OAuth, SSO, role-based access).
Daily use of coding agents, and the discipline to review and validate what they produce.
Comfort and proficiency working directly with non-technical users: asking great questions, learning an unfamiliar business fast, and turning messy processes into working software.
Judgment in security and compliance-sensitive environments. You know what data cannot leave the building and design accordingly.
Clear and effective written and spoken communication. You can write a one-page memo that makes the technical and business case to an executive.

Nice to have

Prior forward-deployed engineering, product management, or early-engineer experience.
Experience integrating enterprise platforms such as Salesforce, Microsoft 365, NetSuite, Jira, and Databricks.
Exposure to SOX, FedRAMP, or similar control environments.
Experience in a security or PKI company, or another business where trust is the product.

Benefits

Competitive compensation and comprehensive health, dental, and vision coverage
Retirement savings programs with company matching (401(k) or RRSP)
Generous paid time off, including holidays, and vacation
Paid parental leave and family support benefits
Life and disability coverage
Flexible spending and health savings options (where applicable)
Health and wellness support, including gym reimbursement and wellness programs
Employee Assistance Program with 24/7 confidential support for employees and families
Education assistance and professional development opportunities
Access to LinkedIn Learning and continuous learning resources
Employee referral bonus program and additional company perks and discounts
Internal rewards and recognition platform ( Motivosity ) to celebrate and acknowledge project wins, milestone achievements, and the outstanding contributions of our colleagues
Business travel insurance and global employee support programs

To protect candidate information and maintain a secure hiring process, all applications must be submitted through our careers portal. Resumes or CVs sent directly via email will not be reviewed or considered.

DigiCert is an Equal Opportunity employer and is committed to diversity in its workforce. In compliance with applicable federal and state laws, DigiCert prohibits discrimination on the basis of race or ethnicity, religion, color, national origin, sex, age, sexual orientation, gender identity/expression, veteran’s status, status as a qualified person with a disability, or genetic information. Individuals from historically underrepresented groups, such as minorities, women, qualified person with disabilities, and protected veterans are strongly encouraged to apply.

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Compensation Transparency:

The annualized base salary range for this position is outlined below.

Each candidate’s compensation offer will be determined based on factors including experience, skills, qualifications, job duties, business needs, and location. For roles that include additional compensation components, total compensation may include base pay, bonus, equity, or other incentives.

This role may also be eligible for benefits, which will be discussed during the hiring process. We are committed to fair and transparent pay practices and comply with all applicable pay transparency requirements. If you would like more information about compensation or benefits, we are happy to provide additional details during the hiring process.

For more information regarding our comprehensive benefits, see the benefits section.

Base Salary

$155,000 - $200,000 USD

🎯 Who is this job for?

Senior-level engineers with at least four years of production software experience and two years building LLM-powered systems are best suited for this role.

They should be skilled in Python or TypeScript/JavaScript, APIs, webhooks, data pipelines, authentication, retrieval, tool calling, agents, context engineering, testing, deployment, observability, and security-conscious system design.

The ideal candidate is comfortable working directly with non-technical stakeholders and should be experienced in mapping business workflows, integrating enterprise systems, shipping and supporting production AI solutions, measuring business impact, and training users.

💬 Potential Interview Questions

How would you identify the highest-value AI opportunities within an unfamiliar business function?

I would interview users, map the current workflow, quantify volume and bottlenecks, and identify where errors, manual effort, or delays create measurable cost. I would prioritize opportunities based on expected ROI, feasibility, data availability, risk, and time to production.

How would you design a production LLM agent that can safely take actions in enterprise systems?

I would constrain the agent with explicit tools, schemas, permissions, validation, audit logging, and human approval for high-impact actions. The system should separate planning from execution and fail safely when context, authorization, or tool results are uncertain.

How would you evaluate and improve the performance of a retrieval-augmented generation system?

I would create a representative evaluation set covering retrieval quality, groundedness, completeness, latency, and cost. Improvements could include better chunking, metadata and hybrid search, query rewriting, reranking, context limits, and targeted prompt changes.

How would you integrate an AI workflow with platforms such as Salesforce, Microsoft 365, Jira, or NetSuite?

I would use supported APIs, webhooks, and event-driven workflows with OAuth or service accounts, while respecting rate limits and platform-specific permissions. I would add retries, idempotency, validation, monitoring, and clear handling for partial failures.

How would you secure sensitive enterprise data used by an LLM application?

I would classify the data, minimize what is sent to models, enforce tenant and role-based access controls, and use approved model endpoints with appropriate retention settings. Secrets, prompts, tool calls, and outputs would be protected through encryption, logging controls, redaction, and regular access reviews.

When would you build an AI solution versus buying or configuring an existing product?

I would compare time to value, total cost of ownership, integration requirements, security and compliance posture, customization needs, vendor lock-in, and maintainability. I would build only where the workflow or differentiation justifies the additional operational responsibility.

How would you introduce human-in-the-loop review into an AI-powered workflow?

I would define risk-based approval thresholds and route low-confidence, ambiguous, or high-impact cases to qualified reviewers. The review interface should show the source context, proposed action, reasoning or evidence, and provide feedback that can improve future evaluations.

What observability would you implement for a production AI application?

I would monitor availability, latency, token usage, cost, tool errors, retrieval quality, model outputs, user corrections, and business outcomes. Traces should connect user requests to retrieval, model calls, tool actions, approvals, and final results without exposing sensitive data unnecessarily.

How would you measure whether an AI solution delivered business value?

I would establish a baseline before launch, such as processing time, error rate, throughput, or labor cost, and compare it with post-launch results. The outcome should be reported as a concrete metric such as hours saved, cycle time reduced, cost avoided, or revenue enabled.

How would you deploy and support an AI service written in Python or TypeScript?

I would use automated testing, code review, CI/CD, environment-specific configuration, infrastructure with least-privilege access, and staged releases. After deployment, I would provide alerting, rollback procedures, runbooks, user feedback channels, and a regular process for reviewing model and workflow performance.

📋 Job Summary

DigiCert is a global leader in intelligent trust, securing digital interactions through its AI-powered DigiCert ONE platform. As a Forward Deployed Engineer, you’ll embed with business teams, identify high-impact opportunities, and build, deploy, and support production AI agents, integrations, and automated workflows using Python or TypeScript/JavaScript, LLMs, retrieval, tool calling, APIs, and enterprise platforms. This is a fully remote US role with a base salary of $155,000–$200,000 USD, plus comprehensive benefits. Apply to own end-to-end solutions, work directly with executives and users, and deliver measurable business impact in a high-growth, high-ownership environment.