Senior Full Stack Developer – AI SaaS

About the role

The company is looking for a Senior Full Stack Developer to own the architecture, development and delivery of its AI-based SaaS products, ranging from conversational and voice agents to RAG pipelines, workflow automation, in-house language models and production at scale. The role leads a full-stack engineering team and reports directly to the Project Lead.

Key responsibilities

• Own the technical architecture, roadmap and platform decisions for multi-tenant AI SaaS products.
• Lead and manage the engineering team, including sprint planning, code reviews, capacity planning and performance management.
• Design and deliver agentic AI systems: tool calling, multi-step workflows, memory, orchestration and human hand-over.
• Architect RAG pipelines end-to-end, from data ingestion and embeddings to vector search, re-ranking and evaluation.
• Evaluate and select LLMs, balancing accuracy, latency, cost and hosting (API vs self-hosted).
• Develop in-house SLMs as data grows: dataset strategy, preparation, fine-tuning, distillation, evaluation and deployment.
• Build real-time voice capabilities with STT and TTS, including streaming and latency optimisation.
• Integrate with WhatsApp Business API, telephony (SIP/WebRTC), CRMs, ERPs and third-party APIs.
• Own production reliability, security, observability and DevOps practices.
• Turn business requirements into technical specs, estimates, backlogs and timelines, with weekly progress and risk reporting.

Required profile

• 6-8+ years in software engineering, including 2+ years leading engineering teams and AI bots.
• Full-stack developer with strong hands-on experience across front end, back end, databases and APIs.
• Proven track record of delivering projects on tight deadlines and owning them end-to-end.
• Proven experience building and scaling a SaaS product in production.
• Bachelor's or Master's degree in Computer Science, Software Engineering, AI or equivalent.
• Excellent English communication; Arabic is a strong plus.

Required skills

• Python (FastAPI/Django) and full-stack (React/Next.js, PostgreSQL, Redis)
• RAG systems, vector databases (pgvector, Pinecone, Qdrant) and frameworks such as LangChain, LangGraph or LlamaIndex
• Knowledge of LLMs (OpenAI, Anthropic, Gemini, Llama, Qwen, Mistral) and prompt engineering, guardrails and evaluation
• Building SLMs from proprietary datasets: fine-tuning (LoRA/QLoRA), distillation, quantisation, benchmarking and serving (PyTorch, Hugging Face, vLLM)
• STT and TTS (Whisper, Deepgram, ElevenLabs, Azure Speech)
• Workflow automation (n8n, Make) and cloud/DevOps (AWS/GCP, Docker, CI/CD, GPU workloads)