AI / GenAI Solutions Engineer

Role Name: AI / GenAI Solutions EngineerLocation: Egypt, Pakistan (Remote)Work Week: Sunday - ThursdayWorking Hours: 9:00 AM - 6:00 PM (Saudi Arabia Standard Time)Overview:Soum is building an AI native layer across our C2C marketplace, from customer conversations to automated order handling, personalised discovery, recommendations, fraud signals, and seller tooling. We're looking for a Senior GenAI Engineer to design and ship production-grade AI systems that touch millions of users across the buying and selling journey.You'll work end-to-end: architecting LLM-powered services on our Python backend, integrating them into product surfaces on our React frontend, and partnering with teams across the company to find where AI genuinely moves the needle. This is a senior builder's role with high autonomy, broad scope, and real impact on the business.What You’ll DoArchitect production GenAI systems across multiple domains, including conversational agents, automated order and dispute workflows, personalized discovery and recommendations, content generation, search relevance, and emerging use cases. Own features end-to-end, from problem framing and model selection through backend services (FastAPI, Python), frontend integration (React, TypeScript), evaluation, deployment, and monitoring. Design agentic workflows with tool calling, multi-step reasoning, retrieval augmented generation, and integrations with internal APIs, third-party SaaS, and event-driven systems. Build the retrieval and embeddings stack, including chunking strategies, embedding model selection, vector indexes, hybrid search, reranking, and retrieval evaluation pipelines. Make it reliable and cost-efficient through streaming, prompt caching, latency budgets, token cost optimization, observability for LLM calls, and graceful fallback when models or upstreams misbehave. Establish evaluation rigor with offline and online evals covering response quality, tool call correctness, hallucination rate, retrieval precision, and business KPIs. Drive experimentation and research by evaluating new models, frameworks, and agent patterns, running focused experiments, and bringing what works into production. Mentor and raise the bar for engineers across the team on AI and ML best practices, prompt engineering, and production readiness. Partner cross-functionally with Product, Engineering, Data, Ops, and CX to identify high-leverage AI opportunities and ship them. Where You'll Have ImpactA non-exhaustive list of areas we are actively building in or want to:Conversational AI for customer support, dispute resolution, and seller assistance Automated order handling, escalation routing, and workflow orchestration Personalized discovery, recommendations, and search relevance Listing quality, including auto-generated titles, descriptions, categorization, and image understanding Trust and safety, including fraud signals, anomaly detection, and content moderation Internal agent tooling for ops and CX teams QualificationsRequired5+ years building production software, with at least 2 years shipping LLM and ML-powered features at scaleStrong Python for backend services, scripting, data pipelines, and ML toolingWorking ability in TypeScript and React for integrating AI features directly into product surfacesProduction experience with major LLM providers (Gemini, Claude, GPT) covering tool and function calling, structured outputs, streaming, prompt caching, and cost controlDeep understanding of Retrieval Augmented Generation (RAG): document ingestion, chunking, embedding generation, vector databases (pgvector, Pinecone, Weaviate, or similar), hybrid retrieval, and rerankingSolid grounding in embeddings and vector search: dense vs. sparse representations, similarity metrics, indexing strategies (HNSW, IVF), and dimensionality tradeoffsStrong ML and NLP fundamentals: transformer architectures, tokenization, fine-tuning vs. prompting tradeoffs, classification, ranking, and evaluation methodologyExperience with scripting and automation for data preparation, model evaluation harnesses, and offline analysisComfortable with relational databases (PostgreSQL), caching layers (Redis), REST, SSE, WebSockets, and event-driven architecturesProduction experience with observability, A/B testing, and rolling out model changes safelyNice to HaveExperience with recommendation systems, learning to rank, or search relevance at scaleMarketplace or C2C background covering buyer and seller dynamics, disputes, fraud, and payoutsMultimodal model experience, including vision and image understanding for listingsArabic NLP or bilingual product experienceExperience with agent frameworks (LangGraph, custom orchestrators) and the judgment to know when to use themFine-tuning, LoRA, distillation, or hosting open weight models in productionOpen source contributions to LLM tooling, eval frameworks, or retrieval librariesWhat We Care AboutShip over the architect. Lean code, no premature abstractions, no half-finished frameworks. Measurement-driven development. Features ship with evals and metrics, not vibes. Ownership. From idea to deployment to monitoring the first real users. Curiosity and range. This role spans many problem domains, and we want someone energized by that. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.