Forward Deployed Engineer

Decision Lens; Arlington (VA); Remote; USD 150,000 - 200,000; Full time

Benefits offered by this job

Commission plan

Job summary

Decision Lens is seeking a Forward Deployed Engineer to embed engineering, data, and application development into customer environments, delivering measurable mission outcomes. Operating at the intersection of product, engineering, and customer experience, you will own problems end-to-end—from discovery to deployment, and leverage AI-assisted tools to accelerate value while maintaining quality.

This remote-first role requires on-site work or travel to customer sites in Arlington, VA area and

Qualifications

• Bachelor’s degree in computer science, engineering, information systems, or a related technical field, or equivalent practical experience.
• 5+ years in software engineering, forward‑deployed or field engineering, technical consulting, or enterprise application delivery.
• Demonstrated ability to build working software end-to-end across frontend, backend, data, and workflow logic.
• Experience working directly with customers in complex environments, translating ambiguous requirements into deployed software.
• Strong understanding of APIs, data modeling, workflow logic, application security, and deployment patterns.
• Hands‑on experience with AI‑assisted development tools, or a demonstrated willingness to adopt them responsibly.
• Eligibility for Secret or above security clearance required; active clearance strongly preferred.
• Travel requirements are based on customer needs and expected to be around 30%.

Responsibilities

• Embed onsite with customers through discovery, trust-building, workflow mapping, solution design, deployment and stabilization.
• Work cross functionally including with CX, engineering, sales, solutions engineering and functional SMEs to understand the customer’s challenges and design the best solution.
• Translate ambiguity into a clear solution to be deployed within Decision Lens.
• Proactively identify when the stated requirement is not the real problem, and ask the few critical questions early that prevent weeks of rework later.
• Design data models that support decision workflows, prioritization, scoring, traceability, auditability, and executive reporting.
• Take personal responsibility for the reliability, security, testing, and quality of everything deployed.
• Use AI coding agents and AI-assisted tools such as Claude Code, Cursor, and GitHub Copilot to accelerate development, testing, debugging, and documentation.
• Prompt, direct, and review AI-generated code while maintaining ownership of architecture, technical decisions, and quality—reviewing, testing, and hardening AI-assisted work before customer delivery.
• Exercise strong judgment about where AI-generated code is useful and where it creates risk, and never expose sensitive customer data or controlled information in unauthorized tooling.
• Run demo-driven development cycles with frequent customer feedback; show working software early and respond constructively when users challenge the application, data, or logic.
• Stay engaged through stabilization until the application is usable, accepted, and has an identified operational owner—then exit cleanly so the solution never becomes permanently dependent on the individual FDE.
• Produce crisp written plans, decision logs, implementation notes, and executive-ready updates, and communicate tradeoffs in business, operational, and mission terms.
• Say “no,” “not yet,” or “phase two” gracefully when scope threatens the timeline, architecture, or mission outcome.
• Identify reusable apps, templates, integration patterns, workflow components, and data models from field engagements, and contribute them back to Decision Lens repositories and playbooks.
• Serve as the voice of the field to Product and Engineering, distinguishing one-off customer‑specific work from repeatable product opportunity.
• Build with reuse and product leverage in mind.

Skills

Software engineering

APIs

Data modeling

Frontend

Backend

AI-assisted development

Customer engagement

Security clearance

Education

Bachelor’s degree in computer science, engineering, information systems, or related technical field

Tools

Claude Code

Cursor

GitHub Copilot

DataHub/AppHub

Tableau

Power BI

Job description

The Forward Deployed Engineer (FDE) is a hands-on builder on the Customer Experience (CX) team who embeds engineering, data, and application development directly into customer environments to deliver measurable mission outcomes. The FDE embeds with customers during time-boxed engagements, learns how their decisions are actually made, and rapidly turns ambiguous needs into production-grade applications on the Decision Lens platform.

Operating at the intersection of product, engineering, and customer experience, the FDE owns problems end-to-end—from discovery and solution design through build, demo, stabilization, and handoff—using modern AI-assisted development tools to accelerate time-to-value without sacrificing engineering discipline. Beyond any single engagement, the FDE institutionalizes reusable patterns and feeds field insights back into the product roadmap, helping Decision Lens scale rather than become a bespoke services organization.

Duties and Responsibilities

Customer Embedding & Workflow Discovery

Embed onsite with customers through discovery, trust-building, workflow mapping, solution design, deployment and stabilization.

Work cross functionally including with CX, engineering, sales, solutions engineering and functional SMEs to understand the customer’s challenges and design the best solution.

Translate ambiguity into a clear solution to be deployed within Decision Lens.

Proactively identify when the stated requirement is not the real problem, and ask the few critical questions early that prevent weeks of rework later.

Application Design & Build

Design and build working applications on the Decision Lens platform in DataHub/AppHub.

Work across the full application stack: frontend, backend, APIs, data layer, workflow logic, and deployment configuration.

Design data models that support decision workflows, prioritization, scoring, traceability, auditability, and executive reporting.

Make pragmatic tradeoffs—speed versus scope versus scalability—and deliver quickly, then iterate from customer feedback toward operational readiness.

Take personal responsibility for the reliability, security, testing, and quality of everything deployed.

AI-Assisted Development

Use AI coding agents and AI-assisted tools such as Claude Code, Cursor, and GitHub Copilot to accelerate development, testing, debugging, and documentation.

Prompt, direct, and review AI-generated code while maintaining ownership of architecture, technical decisions, and quality—reviewing, testing, and hardening AI-assisted work before customer delivery.

Exercise strong judgment about where AI-generated code is useful and where it creates risk, and never expose sensitive customer data or controlled information in unauthorized tooling.

Run demo-driven development cycles with frequent customer feedback; show working software early and respond constructively when users challenge the application, data, or logic.

Stay engaged through stabilization until the application is usable, accepted, and has an identified operational owner—then exit cleanly so the solution never becomes permanently dependent on the individual FDE.

Produce crisp written plans, decision logs, implementation notes, and executive-ready updates, and communicate tradeoffs in business, operational, and mission terms.

Say “no,” “not yet,” or “phase two” gracefully when scope threatens the timeline, architecture, or mission outcome.

Reuse & Product Feedback

Identify reusable apps, templates, integration patterns, workflow components, and data models from field engagements, and contribute them back to Decision Lens repositories and playbooks.

Serve as the voice of the field to Product and Engineering, distinguishing one-off customer‑specific work from repeatable product opportunity.

Build with reuse and product leverage in mind.

Job Qualifications

Required

Bachelor’s degree in computer science, engineering, information systems, or a related technical field, or equivalent practical experience.

5+ years in software engineering, forward‑deployed or field engineering, technical consulting, or enterprise application delivery.

Demonstrated ability to build working software end-to-end across frontend, backend, data, and workflow logic.

Experience working directly with customers in complex environments, translating ambiguous requirements into deployed software.

Strong understanding of APIs, data modeling, workflow logic, application security, and deployment patterns.

Hands‑on experience with AI‑assisted development tools, or a demonstrated willingness to adopt them responsibly.

Eligibility for Secret or above security clearance required; active clearance strongly preferred.

Travel requirements are based on customer needs and expected to be around 30%.

Preferred

Active Secret, TS, or TS/SCI clearance.

Experience in DoW, IC, defense technology, or government consulting.

Familiarity with PPBE, portfolio management, or decision‑support constructs.

Experience with multi‑criteria decision frameworks (weighted scoring, MAUT, AHP), LLMs, AI agents, or configurable workflow platforms.

Familiarity with the Decision Lens platform, Tableau, Power BI, or similar decision‑support and analytics environments.

Experience building reusable frameworks, templates, or accelerators.

Location: Decision Lens operates in a remote‑first environment. Our headquarters are located in Arlington, VA. This role is on the Customer Experience team and requires on‑site work and/or travel at customer locations driven by customer needs and contractual requirements.

Compensation: The base salary range for this position is $150,000–$200,000 per year. The range reflects that this role may be filled at varying seniority levels; actual compensation will be determined by factors including relevant experience, skills, qualifications, security clearance, and internal equity. This position is also eligible to participate in a commission plan.

Company Overview

Decision Lens is an AI‑driven platform for high‑stakes government decisions, built to give leaders the clarity, speed, and analytical rigor that hard choices between competing priorities demand.

Behind every government budget, program, or policy tradeoff is a leader and a team accountable for the outcome, often working with incomplete information and competing pressures. That's the problem we've dedicated ourselves to solving.

Decision Lens establishes a governed decision framework that connects real‑time data to the criteria and rationale behind every decision, so leaders can make better, faster tradeoffs with confidence and defend them at any point in time.

Decision Lens Inc is an equal opportunity employer, and as such affirms the right of every person to participate in all aspects of employment without regard to race, religion, color, national origin, citizenship, sex, age, veteran status, disability, genetic information, or any other protected characteristic.