AI & Backend Developer with 2+ years of professional experience designing and deploying scalable, production-grade AI systems and backend services. Specialised in building REST APIs and microservice architectures, real-t…
AI & Backend Developer with 2+ years of professional experience designing and deploying scalable, production-grade AI systems and backend services. Specialised in building REST APIs and microservice architectures, real-time audio processing pipelines, LLM integrations, and Retrieval-Augmented Generation systems. Proven track record of owning projects end-to-end, from backend architecture and API development through to cloud deployment and production monitoring, with a strong foundation in Python, Docker, and distributed workflow orchestration.
<p>Engineered high-performance gRPC services and REST APIs for real-time voice processing, achieving sub-50ms end-to-end latency for live audio streams at scale.<br>
Designed and integrated custom processors within the Pipecat microservices pipeline to orchestrate multi-service data flow, enabling the MYNA platform to handle concurrent voice sessions reliably.<br>
Led the training and production deployment of custom TTS models.<br>
Built auxiliary models for emotion recognition and language detection, improving call naturalness scores by ~25%.<br>
Architected an automated call evaluation framework scoring voice-call success through intent analysis and response accuracy.<br>
Optimised LLM prompts to reduce hallucination rates in production dialogues.<br>
Implemented Google Calendar API handlers for automated scheduling workflows.<br>
Integrated Meta Graph API to extend platform reach across Instagram and Messenger.<br>
Contributed to the design and development of a subscription-based billing system supporting recurring SaaS payments, handling financial data flows and transaction logic.<br>
Optimised asynchronous real-time data flow using WebSockets, improving responsiveness and connection stability across concurrent sessions.</p>
Engineered high-performance gRPC services and REST APIs for real-time voice processing, achieving sub-50ms end-to-end latency for live audio streams at scale., Designed and integrated custom processors within the Pipecat microservices pipeline to orchestrate multi-service data flow, enabling the MYNA platform to handle concurrent voice sessions reliably., Led the training and production deployment of custom TTS models; built auxiliary models for emotion recognition and language detection, improving call naturalness scores by ~25%., Architected an automated call evaluation framework scoring voice-call success through intent analysis and response accuracy; optimised LLM prompts to reduce hallucination rates in production dialogues., Implemented Google Calendar API handlers for automated scheduling workflows; integrated Meta Graph API to extend platform reach across Instagram and Messenger., Contributed to the design and development of a subscription-based billing system supporting recurring SaaS payments, handling financial data flows and transaction logic., Optimised asynchronous real-time data flow using WebSockets, improving responsiveness and connection stability across concurrent sessions.
<p>Designed and deployed a scalable enterprise RAG platform using open-source LLMs and Milvus vector database with hybrid semantic search, enabling employees to query 100+ internal documents with high accuracy.<br>
Integrated Nvidia NeMo Guardrails to secure LLM outputs and eliminate prompt injection risks in a regulated production environment, reducing security incidents to zero.<br>
Architected multi-node workflow orchestration using Apache Airflow, Celery, and RabbitMQ, containerised with Docker, improving pipeline reliability, retry handling, and operational resilience across distributed nodes.<br>
Applied quantization techniques (INT8/GGUF) to enable high-throughput LLM inference on CPU-bound infrastructure, reducing inference costs while maintaining response quality.</p>
Designed and deployed a scalable enterprise RAG platform using open-source LLMs and Milvus vector database with hybrid semantic search, enabling the employees to query 100+ internal documents with high accuracy., Integrated Nvidia NeMo Guardrails to secure LLM outputs and eliminate prompt injection risks in a regulated production environment, reducing security incidents to zero., Architected multi-node workflow orchestration using Apache Airflow, Celery, and RabbitMQ, containerised with Docker, improving pipeline reliability, retry handling, and operational resilience across distributed nodes., Applied quantization techniques (INT8/GGUF) to enable high-throughput LLM inference on CPU-bound infrastructure, reducing inference costs while maintaining response quality.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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