Forward Deployed Engineer, R&D Ai Automation
Abu Dhabi (UAE)
· Member of Technical Staff
· Engineer II, L4
· MJD
02.0.1
This role is deployed into that reality on behalf of the R&D team, with no finished product to install: sit with domain experts, record how they work, and turn what you see into structure that has to hold.
Workflow models. Evaluation tasks from a single action to a whole task. Fault specifications for simulated copies of the applications. Demonstration recordings.
What fails on real applications comes back to the team as a specification. Progress is measured against benchmarked results.
KEY RESPONSIBILITIES- Observe and record how domain experts operate their applications, and elicit what the recordings do not show
- Decompose workflows into explicit structure: states, decisions, exceptions and failure modes, generalised across applications
- Turn that structure into artefacts that must work: evaluation tasks, fault specifications for simulated applications, demonstration recordings
- Run the feedback loop from real applications to the R&D team; build quick prototypes and demonstrations
- Has worked embedded with expert users on behalf of an engineering or research team, and can say what the users could not tell them
- Has turned a messy, undocumented human process into a specification that a team implemented and that held in production
- Has built evaluation tasks or simulated environments from real workflows
- Has recorded and analysed how third-party web applications behave (network logs, Dev Tools, screen recordings) to diagnose failures
- Patient and precise with people who have no documented process; runs discovery sessions with non-technical experts
- Thinks in states, decisions and exceptions, and treats the happy path as the easy part
- Daily use of AI coding tools, including reviewing and verifying their output
- Presents working demonstrations to non-technical audiences
- Product engineering: we own what we build and run it in production
- Small teams, two-week cycles, working software at every review
- AI coding tools are part of the standard workflow
- AI-augmented engineering environment
- Access to on-premise Nvidia B200s
- Flexible work environment
- Practical session; the format is agreed with you
In coding exercises, AI tools are allowed and expected. No Leet Code.
WHO WE ARENew product organisation as part of a large semi-government in Abu Dhabi. International, ex-FAANG team. Completely greenfield, with a modern tech stack.
REQUIREMENTS TO BE CONSIDERED- Fluent Arabic and English, spoken and written
- 3+ years in an engineering role with direct contact with the people who use what you build
- Own code operated in production; comfortable in Type Script or Python
- Bachelor's degree in any field, or self-taught with a track record of open-source contributions
- Session capture and replay: rrweb, HAR, WARC, screen recording
- Evaluation: evaluation harnesses, trajectory evaluation, LLM-as-judge, Inspect, Langfuse; benchmarks such as Online-Mind2
Web, Web Arena, OSWorld - Process analysis: task mining, process mining, cognitive task analysis, behaviour-driven specification (Gherkin), state machines
- Models and infrastructure: open-weight LLMs, vLLM, SGLang, Kubernetes, Type Script, Python
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