AI & Data Engineer
TechLabs London
full-time
Posted on:
Location Type: Hybrid
Location: Cairo • Egypt
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Tech Stack
About the role
- Design and build end-to-end AI pipelines across use cases such as predictive modelling, NLP, computer vision, and conversational AI.
- Design, develop and deploy conversational AI solutions using LLMs and agentic frameworks (e.g. LangChain, LangGraph), including RAG pipelines, intent classification, entity extraction, and multi-turn dialogue management.
- Apply computer vision to extract intelligence from images and videos for detection, classification, and automation.
- Develop time-series models that analyze behavior and generate predictive insights.
- Experiment with foundational models and fine-tune them for specific tasks relevant to our domain.
- Integrate models into production by working with our developers to deploy solutions into our products and beyond.
- Architect and build scalable, secure, and reusable ML APIs, workflows, and pipelines using modern MLOps practices and containerisation (Docker).
- Translate business problems into data-driven solutions, working closely with product, customer success, and engineering teams.
- Champion AI-first thinking across the company, supporting POCs, internal tooling, and customer-facing features.
- Collaborate with internal developers, product managers, domain experts, and external stakeholders to ensure solutions are feasible, maintainable, and impactful, as well as to define data strategies and model objectives.
- Conduct rigorous A/B testing and model evaluation.
- Support the integration of models into production systems using APIs and microservices.
- Stay abreast of advancements in AI/ML research and apply relevant breakthroughs to ongoing projects.
Requirements
- Bachelor’s degree in information technology, Software Engineering, Computer Science, or related field.
- Proven experience building and deploying LLM-powered applications, including RAG pipelines and conversational agents.
- Hands-on experience with LangChain or similar agentic frameworks (LangGraph, AutoGen, or equivalent).
- Strong proficiency in Python and relevant ML libraries (e.g. pandas, scikit-learn, PyTorch, spaCy, Hugging Face, OpenCV etc.)
- Experience with cloud platforms — Azure is our primary platform (preferred); AWS or GCP also considered.
- Containerization and orchestration: Docker, Docker Compose.
- Solid understanding of data modelling, feature engineering, and data warehousing concepts.
- Strong knowledge of SQL and experience with relational and/or vector databases (e.g. pgvector, Pinecone, Weaviate).
- Proficiency in version control, CI/CD, and model deployment practices.
- Experience integrating AI models into web or mobile applications is highly valued.
- Experience with MLOps tools like MLflow, Airflow, DVC.
- Familiarity with MCP Server (Model Context Protocol) for building tool-augmented AI agents is a plus.
- Strong problem-solving and analytical thinking — able to translate messy real-world data into measurable solutions.
- Pragmatic and delivery-oriented — capable of balancing technical innovation with business impact.
- Communicative and collaborative — comfortable working across teams and disciplines.
- Self-driven — able to manage time, priorities, and project ownership in a fast-moving team.
- Knowledge of data governance, bias mitigation, and explainable AI techniques.
Benefits
- Flexible working arrangements
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonLLM-powered applicationsRAG pipelinesLangChainLangGraphpandasscikit-learnPyTorchspaCyOpenCV
Soft Skills
problem-solvinganalytical thinkingpragmaticdelivery-orientedcommunicativecollaborativeself-driven