AI Tech Lead

Lucidya | لوسيديا

. Own and be accountable for the AI architecture and harness, including model selection, prompting patterns, retrieval design, guardrails, and voice pipeline .

Posted 10/21/2026full-timeRemote • Saudi ArabiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI architecture, model selection, and production-level LLM applications, with a strong focus on mentoring and technical leadership. Proficient in building evaluation pipelines and ensuring quality in AI systems through effective monitoring and debugging.

Highest-signal resume keywords

AI Architecture OwnershipLLM-Based Application DevelopmentTechnical LeadershipPython ProgrammingProduction Monitoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning EngineeringPrompting PatternsModel Evaluation PipelinesGuardrails DevelopmentAgent PatternsDebugging Distributed SystemsCloud DeploymentObservabilityTechnical DocumentationExperimentation Management

Soft Skills

MentoringProblem-SolvingCommunicationAdaptability

Tools & Technologies

APIsReal-Time Voice AgentsASRTTSLangfuseArize

Industry Keywords

AI Platform-Level ExperienceLLM EvaluationVoice AINLPGulf Arabic

Tech Stack

Tools & technologies

CloudDistributed SystemsPython

About the role

Key responsibilities & impact

Own and be accountable for the AI architecture and harness, including model selection, prompting patterns, retrieval design, guardrails, and voice pipeline
Make and document technical decisions with clear rationale
Define the evaluation standard and move key work from experimentation to production
Introduce leading testing frameworks for Agentic development
Ensure production monitoring and online evaluations catch quality drops, hallucinations, and latency spikes before customers report them
Lead the AI team in designing, developing, and delivering Lucidya's Agentic Platform
Mentor AI engineers, raise the technical bar through pairing and feedback, and contribute to hiring
Lead debugging of critical production incidents involving AI behavior
Manage prototypes and experiments to validate new models, agent patterns, and voice features
Work with Product to turn customer use cases into technical requirements
Work with Engineering on shared platform work including tool calling, workflows, deployment, and scaling

Requirements

What you’ll need

7+ years in software or ML engineering, including 2+ years building LLM-based applications in production
AI platform-level experience, not just AI point solutions
Technical leadership of a team of 3+ AI engineers/scientists, including design reviews, standards, and mentoring
Deep hands-on experience with prompting, structured outputs, guardrails, agent patterns, and harness development (planning, tool use, multi-step reasoning)
Ability to work in ambiguous settings and bring clarity and structure to complex situations
Experience building LLM evaluation pipelines, including golden datasets, LLM-as-judge, and regression suites, and using them to gate releases
Strong Python
Experience with APIs, cloud deployment, observability, and debugging distributed systems
Fluent written and spoken English
Ability to write clear design docs and decision records
Nice to have: Arabic NLP experience, especially Gulf Arabic, in LLM or speech systems
Nice to have: Voice AI experience with ASR, TTS, real-time voice agents, and latency optimization
Nice to have: Hands-on use of LLM tracing and online evaluation tools such as Langfuse, Arize, or similar
Nice to have: Fine-tuning or distilling open-weight models and serving them cost-effectively