Forward Deployment Engineer (FDE)

Forward Deployment Engineer (FDE) Technology / Business Process

Remote

Contract

Job Description

We are seeking experienced Forward Deployment Engineers (FDEs) to work at the intersection of technology, engineering, and business processes. The FDE will partner closely with business stakeholders, customers, product teams, and engineering teams to understand complex operational challenges and deploy technology solutions that solve real-world business problems.

The ideal candidate combines strong software/technology skills with business process understanding and can move effectively from requirements and process discovery through solution design, implementation, testing, deployment, and production support.

Key Responsibilities

• Work directly with customers and business stakeholders to understand business processes, operational challenges, and technology requirements.
• Translate business problems into technical solutions, workflows, integrations, and automation opportunities.
• Design, configure, develop, and deploy solutions in customer or enterprise environments.
• Conduct process discovery, requirements gathering, workflow analysis, and gap analysis.
• Develop prototypes and proof-of-concepts to validate proposed solutions.
• Integrate enterprise applications, APIs, databases, SaaS platforms, and internal systems.
• Build automation and tools using Python, Java, JavaScript/TypeScript, SQL, APIs, and cloud services as appropriate.
• Work with engineering and product teams to convert field requirements into product enhancements and scalable capabilities.
• Troubleshoot complex technical and business-process issues in production environments.
• Analyze data, logs, workflows, and system behavior to identify root causes and recommend solutions.
• Configure and deploy solutions across cloud, on-premises, and hybrid environments.
• Develop technical documentation, process documentation, runbooks, and implementation guides.
• Support UAT, deployment, production rollout, and post-production stabilization.
• Identify opportunities for AI/GenAI, automation, workflow optimization, and digital transformation.
• Establish reusable implementation patterns and best practices that can be applied across multiple customers or business units.
• Collaborate with Product, Engineering, Architecture, Data, Security, QA, and Customer Success teams.
• Communicate technical concepts and solution trade-offs clearly to both technical and non-technical stakeholders.

Required Skills

• 4+ years of experience in software engineering, solutions engineering, technology consulting, implementation engineering, or a similar role.
• Strong experience working directly with customers or business stakeholders.
• Strong understanding of business processes, workflow analysis, and technology-enabled process transformation.
• Hands-on programming experience with one or more languages such as Python, Java, JavaScript/TypeScript, C#, or Go.
• Strong knowledge of REST APIs, web services, system integrations, databases, and SQL.
• Experience deploying and troubleshooting applications in cloud or hybrid environments.
• Experience with AWS, Azure, or GCP.
• Strong analytical and problem-solving skills with the ability to investigate ambiguous and complex problems.
• Ability to independently take a problem from discovery solution design development deployment production support.
• Excellent communication and stakeholder-management skills.

Preferred Skills

• Experience with Generative AI, LLMs, RAG, AI agents, or AI-powered automation.
• Experience with Docker, Kubernetes, CI/CD, Git, Terraform, or other DevOps technologies.
• Knowledge of data engineering, ETL/ELT, data pipelines, and analytics.
• Experience integrating CRM, ERP, workflow, or enterprise business applications.
• Familiarity with microservices and event-driven architectures.
• Experience with process automation/RPA.
• Experience working in consulting, professional services, SaaS, or enterprise technology environments.
• Ability to operate effectively in fast-changing and ambiguous environments.