Archived listing. The details below describe a past opening.
Forward Deployment Engineer
Role Type: Full-Time / TandM 40/hrs. a week/ day shift
Salary: To be negotiated
Experience: A minimum of 5 years experience
Education: PHD
To apply for this role, please send your resume to
hello@dolgo.ai
Company Overview DOLGO's mission is to preserve the mission-critical expertise that keeps maritime operational through a technology-, data-, and human-centered approach. We are a Synthetic Anthropology business which, in simple terms, is the study of sociology with artificial intelligence and computational modeling
The Role Field experience working as a Forward Deployed Engineer on how to deploy complex software into legacy heavy-industry environments.
- Field Engineering and Edge Computing: Proven experience deploying complex software, IoT, or AI systems in physical, legacy, or heavy-industry environments. You know how to troubleshoot distributed systems outside the comfort of a standard office network.
- Complexity Science and Applied Mathematics: A strong foundational understanding of network effects, non-linear system dynamics, and graph theory. Mathematically model human and operational networks to identify knowledge transfer.
- Distributed Systems and API Architecture: Architecting API-driven backends capable of ingesting data from legacy tools and modern communication platforms while orchestrating the flow of tacit, tribal, and Implicit knowledge.
Output from the role
- Computational Anthropology and Qualitative Data Engineering: Translating ethnographic field observations and human-in-the-loop social dynamics into programmable logic, UI/UX workflows, and algorithmic constraints.
- Human-Computer Interaction HCI and UI/UX Translation: Translating qualitative, ethnographic field data into hard programmable logic and UI adjustments.Ability to rapidly prototype or script front-end workflow modifications on-site to reduce operational friction for users wearing heavy PPE or working in restricted spaces.
Most critical technical capabilities
- Edge Computing and Distributed Systems Engineering: Ability to deploy, monitor, and troubleshoot software on local edge devices, rugged hardware, and mobile units in environments with intermittent, low-bandwidth, or zero-trust connectivity.
- Multimodal Data Capture and IoT Troubleshooting: Hands-on technical ability to configure, calibrate, and debug hardware-to-software integrations for acoustic capture (walkie-talkies, microphones), visual telemetry, and mobile endpoints.
- Network Mathematics and Graph Theory: Applied mathematical skills to model non-linear sociotechnical systems and structural workforce dependencies.