$150,000–$175,000
Forward Deployed Engineer
Published
Pay not postedUSRemote
A customer-facing Forward Deployed Engineer builds production-grade integrations and full-stack solutions directly within strategic clients' technical environments.
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At a glance
Posted base pay
Not posted
Median $188K
Typical senior FDE payMiddle 50% of 1,802 postings$160K–$218KThe work
Builds what the customer runs
Balance
- Mostly building
- Mixed
- Mostly pre-sales or support
Project stages
- Pre-sales (not covered)
- Proof of concept
- Implementation
- Operations
- Coding
- Writes production code
- Builds for
- External customers
- Level
- Senior
- Role
- Individual contributor
What they ask for
Experience
Background
Tools
Less common in FDE jobs
- Fully remote29%
- Covers proofs of concept39%
Share of US FDE postings that state each fact.
The job description from Dura Digital
About Dura Digital
Dura Digital is a global digital transformation and consulting company that helps organizations turn emerging technologies into practical business outcomes. We bring together strategy, human-centered design, engineering, and AI expertise to create solutions that improve operations, customer experiences, and organizational performance.
As a Dura Digital consultant, you will represent our commitment to thoughtful innovation, strong client partnership, and high-quality delivery while working closely with the client’s leadership and delivery teams.
About the role
We are looking for a highly skilled and customer-facing Forward Deployed Engineer (FDE) to bridge the gap between our core engineering team and our most strategic clients. In this role, you will not sit on the sidelines; you will deploy directly to the front lines, working deeply within our customers' technical ecosystems.
You will be responsible for understanding complex customer problems, architecting bespoke solutions, and writing production-grade code that integrates seamlessly with existing systems, data, and workflows. Increasingly, this will include designing and implementing AI-enabled applications, agentic workflows, and intelligent automation alongside traditional software engineering.
If you enjoy solving difficult technical problems, working directly with customers, and seeing the immediate real-world impact of what you build, this role is for you.
Key Responsibilities
- Technical Integration: Scope, architect, and build robust integrations and custom features to connect our platform with client infrastructure.
- Client Collaboration: Work directly with technical stakeholders and executives at client companies to understand their workflows and pain points.
- Full-Stack Development: Write clean, maintainable, and production-ready code across the entire stack.
- AI Implementation: Design and implement AI-enabled solutions using large language models, agents, structured outputs, tool calling, and other emerging AI patterns where appropriate.
- AI Evaluation & Reliability: Develop approaches for evaluating AI systems, including quality, accuracy, latency, cost, security, and reliability, and help determine when AI—or traditional software—is the right solution to a problem.
- Rapid Prototyping to Production: Quickly translate ambiguous business problems into working prototypes, validate solutions with users, and evolve successful concepts into secure, scalable, production-ready systems.
- Feedback Loop: Act as the voice of the customer back to our internal Product and Core Engineering teams to influence the product roadmap.
- Technical Onboarding: Guide clients through the deployment phase, ensuring optimal performance, scalability, and security.
- Troubleshooting: Diagnose and resolve complex technical issues in real-time within highly constrained client environments
Required Qualifications
- Experience: 3+ years of experience in software engineering, solutions architecture, or a technical customer-facing engineering role.
- Technical Stack: Proficiency in at least one major backend language (e.g., Python, Go, Java, C++) and modern frontend frameworks (e.g., React, Vue).
- Infrastructure & Cloud: Strong experience with cloud providers (AWS, GCP, or Azure), Docker, and Kubernetes.
- Data Integration: Solid understanding of APIs (REST, GraphQL), databases (SQL/NoSQL), and data pipelines.
- Communication: Exceptional verbal and written communication skills in English, with the ability to explain complex technical concepts to non-technical stakeholders.
Preferred Qualifications
- Deep knowledge of cybersecurity best practices and data privacy regulations.
- Background in consulting or systems integration.
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Pay not posted
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