REMOTE. TECHNICAL. GLOBAL.
Careers at RAUZ | Engineering, IoT, Embedded & AI
Join RAUZ to build environmental and engineering monitoring intelligence across IoT, embedded systems, AI, software, remote sensing, data analytics and independent technical review through remote-first global collaboration.
Careers at RAUZ
Build the intelligence layer between the physical world and technical decisions.
RAUZ is the Environmental & Engineering Monitoring Intelligence Platform of Rauz Caucasus LLC, based in Tbilisi, Georgia and designed for international, remote-first delivery. Our work connects engineering monitoring, environmental observations, IoT, embedded systems, remote sensing, data, software and AI so that field evidence can be checked, interpreted and turned into useful technical decisions.
Understand physical behaviour
Work with ground movement, groundwater, structures, environmental conditions, sensor behaviour and project context rather than treating measurements as isolated numbers.
Connect sensors to usable information
Build reliable data paths from field devices, monitoring systems and remote-sensing sources into structured workflows that can be checked, analysed and reviewed.
Make technical review more scalable
Use software, automation and AI to reduce repetitive work, identify patterns and improve review consistency while keeping consequential engineering interpretation reviewable.
Long-Term Talent Call
Remote technical talent. Applications welcome worldwide.
RAUZ maintains an ongoing talent channel for specialists who may fit current or upcoming engineering and technology work. The channel is intentionally long-term: we want to know capable people before every project need is fully formed.
Send a concise CV and, where useful, a portfolio, GitHub profile, technical note, project summary or publication. Put the discipline you are applying for in the subject line.
Open channel does not mean every role is continuously vacant.
Applications are reviewed against real technical needs and do not guarantee an immediate interview, assignment or paid role. When a suitable need exists, RAUZ can contact candidates whose experience fits the scope.
Priority Recruitment Areas
IoT, embedded systems and AI are the current long-term technical focus.
These disciplines sit close to RAUZ’s core problem: moving from raw environmental and engineering observations toward stronger field connectivity, edge processing, automated QA/QC and monitoring intelligence.
Field connectivity & monitoring systems
- Design practical IoT architectures for environmental and engineering monitoring.
- Integrate sensors, data loggers, gateways and cloud endpoints.
- Work with serial, IP and wireless interfaces used by real field devices.
- Design acquisition, buffering, synchronisation and device-health workflows.
- Support remote configuration and resilient operation under intermittent connectivity.
- Prototype proof-of-concept systems and document interfaces for productisation.
- Connect measurements to RAUZ data and analytical workflows.
Devices, firmware & edge processing
- Develop firmware for microcontroller-based monitoring or field-access devices.
- Interface with digital and analogue sensors, ADCs, memory, clocks and communications modules.
- Design low-power operating modes, wake/sleep logic and fault-tolerant data handling.
- Support BLE, Wi-Fi, cellular or other suitable communication stacks where required.
- Implement local filtering, quality checks and lightweight edge processing.
- Test prototypes against realistic field conditions and document failure modes.
- Collaborate on hardware selection, enclosure constraints, power architecture and manufacturability.
Time-series intelligence for real-world monitoring
- Develop anomaly-detection and time-series analysis workflows for monitoring data.
- Build features around trend, rate, change points, missing data and cross-sensor relationships.
- Evaluate AI/ML methods against engineering usefulness, false positives and data limitations.
- Explore lightweight inference or rule-assisted intelligence at the edge where appropriate.
- Support automated QA/QC, data triage and engineer-reviewed reporting.
- Build reproducible experiments, validation datasets and model-evaluation workflows.
- Keep human review visible where technical conclusions affect engineering decisions.
Broader Talent Areas
The platform needs more than one kind of engineer.
RAUZ is multidisciplinary by design. Beyond the current long-term IoT, embedded and AI talent focus, project work may require specialists across monitoring engineering, environmental systems, remote sensing, software, data and technical product delivery.
Geotechnical & Engineering Monitoring
Environmental Monitoring
Agricultural Monitoring
InSAR & Remote Sensing
Software & Data Engineering
Technical Product & Client Solutions
What You May Work On
Real monitoring problems where engineering and technology meet.
A role may sit mainly in one discipline or cross several. The common thread is that the output must help turn field observations into reliable, reviewable information.
Monitoring Intelligence
Review time-series data, baselines, rates, thresholds, instrument consistency and project context to identify what deserves technical attention.
Data Diagnostics
Investigate sudden shifts, missing data, drift, unexplained groundwater trends, conflicting sensors or questionable trigger exceedances.
Remote Sensing Integration
Bring satellite-derived movement into a wider evidence chain rather than treating InSAR as a standalone conclusion.
Connected Field Systems
Prototype sensor interfaces, low-power acquisition, gateway logic, health monitoring and resilient field-to-cloud communication.
AI-Assisted QA/QC
Build tools that screen abnormal patterns, missing data, rate changes and cross-sensor inconsistencies before technical review.
Automated Reporting
Turn repeatable charting, calculations, comparisons and data checks into auditable workflows that reduce manual reporting effort.
Why RAUZ
Small teams can work on unusually broad technical problems.
RAUZ is not structured around a large field workforce. The platform is built around specialist knowledge, remote collaboration, technical systems and repeatable intellectual work. That changes what a strong contributor can own.
Engineering and software meet.
An embedded engineer may need to understand sensor behaviour. A monitoring engineer may help define an AI feature. A data engineer may need to preserve an instrument baseline correctly.
Useful outputs should move beyond slides.
Work may become a technical workflow, internal tool, field prototype, client-facing service, analytical module or repeatable product capability.
Based in Tbilisi. Designed to work across borders.
RAUZ is operated by Rauz Caucasus LLC in Tbilisi, Georgia, while the platform is designed for projects, collaborators and technical specialists across different countries and time zones.
Work Model
Remote-first by design, with project requirements stated clearly.
Many RAUZ technology, analytical and engineering-review tasks can be organised remotely. That does not mean every assignment has identical conditions. A project may impose time-zone, travel, confidentiality, client-access, security or jurisdictional requirements.
Work where the task allows
Software, data, AI, research, engineering review and many embedded-development tasks can often be organised remotely.
International applicants
Applications are welcome from different countries. Contracting, payment, taxation and work-authorisation requirements depend on the actual arrangement and jurisdiction.
Part-time or project-based
Some needs may be suited to part-time, contract or milestone-based collaboration rather than a conventional permanent position.
Field reality still matters
Prototype validation, commissioning, troubleshooting or project delivery may occasionally require local support or agreed travel.
What We Value
Technical judgement matters more than a long software list.
The strongest candidates can explain why they made a technical choice, what evidence supported it, where it could fail and how they tested it.
- Evidence before assumption
- Data quality before interpretation
- Practical engineering judgement
- Clear technical writing
- Ability to work across disciplines
- Comfort with uncertainty and limitations
- Reproducible code or engineering work
- Testing rather than demo-only thinking
- Independent thinking without unnecessary complexity
- Respect for confidentiality and client information
Application Process
Make it easy for us to understand what you can actually build or solve.
For the ongoing remote talent call, email [email protected]. Keep the first application concise and evidence-based.
Name your discipline
Use a clear subject such as “IoT Engineer — Remote”, “Embedded Systems Engineer — Remote” or “AI / Edge AI Engineer — Remote”.
Send concise evidence
Attach a CV and add links to relevant code, prototypes, publications, project summaries or technical portfolios where available.
Explain one hard problem
Briefly describe a technical problem you personally worked on, your role, the trade-offs and what you learned from the result.
Match to real work
If a suitable current or upcoming need exists, RAUZ can contact you to discuss scope, availability, working arrangement and next steps.
For future openings and technical updates, follow the RAUZ company page on LinkedIn and revisit rauzs.com. Specific vacancies may also be published as dedicated job pages when a role has defined employment terms, location requirements or project responsibilities.
Official Industry Context
Monitoring careers increasingly combine engineering, data and digital systems.
The RAUZ talent model reflects a wider pattern visible in official career material from established monitoring, geo-data, infrastructure software and IoT organisations. These references are provided for industry context only and do not imply partnership, endorsement or commercial relationship with RAUZ.
Engineering, monitoring and digital expertise
Sixense’s official careers material describes teams drawn from construction, industrial and digital backgrounds and highlights technicians, engineers and developers working around technical expertise, monitoring and digital solutions.
Official Sixense Careers ↗Geo-data interpretation and AI workflows
Fugro’s official job material shows geotechnical roles involving data processing, interpretation and reporting, alongside AI/ML roles that build and deploy production AI, machine-learning and automation solutions.
Official Fugro Careers ↗Infrastructure software and AI careers
Bentley’s official careers pages highlight software development, AI and infrastructure technology, showing how software and data capabilities increasingly sit alongside traditional engineering workflows.
Official Bentley Careers ↗IoT engineering for safer infrastructure
Worldsensing’s official careers page presents an international IoT team built around innovation, responsibility, teamwork and technical improvement—relevant context for connected monitoring systems.
Official Worldsensing Careers ↗FAQs
Before you apply.
Is RAUZ currently recruiting IoT, embedded and AI engineers?
Is recruitment open internationally?
Are the roles fully remote?
Do I need geotechnical experience?
Can students or early-career engineers apply?
What should I send besides a CV?
Are all opportunities full-time permanent roles?
Where is RAUZ based?
Work With RAUZ
If your work sits between sensing, data and technical judgement, introduce yourself.
RAUZ is interested in people who can make real monitoring systems more reliable, interpretable and useful. A short, technically specific introduction is more useful than a generic cover letter.
Use a clear subject line identifying your discipline and preferred working arrangement.
Not applying for a role?
Technology companies, engineering firms, universities and specialists can use the RAUZ Partnerships route for research, integration, pilots or capability-based collaboration.
RAUZ Partnerships →