About The Role
We are seeking an experienced AI/LLM Full-Stack Engineer to engage as an external contractor with our Gas Services Team in Cairo, Egypt . This role spans the full lifecycle of enterprise AI solutions -from strategic use-case identification and rapid prototyping through to scalable cloud deployment and ongoing application support. The ideal candidate brings a proven track record of delivering LLM-powered applications in production environments and the communication skills to work closely with engineering stakeholders as a trusted digital consulting partner.
A SNAPSHOT OF YOUR DAY
You will be embedded within the Gas Services Middle East Digital team, owning end-to-end delivery of LLM application workstreams. A typical week might involve aligning with stakeholders on a new digital use case, leading a sprint to extend a RAG pipeline, reviewing a junior developer's API integration, and resolving a support ticket all while driving digitalisation of manual efforts in the business.
How You'll Make An Impact
Full-Stack Development & Integration
- Design, build, and deploy robust, scalable full-stack applications integrating React/HTML front-ends with Python/FastAPI back-end LLM services.
- Develop and manage RESTful APIs to embed AI models into existing engineering platforms and enterprise workflows.
- Implement and manage digital pipelines to automate testing and deployment ensuring full compliance to ISO27001 and Cybersecurity/AI Governance standards.
- Collaborate with and provide technical guidance to internal team members, ensuring alignment with project standards, security requirements, and delivery timelines.
AI Application Strategy & Prototyping
- Partner with engineering stakeholders to identify and evaluate high-value opportunities for LLM-based applications(Open AI/Claude) addressing real operational and business needs.
- Translate user requirements and process challenges into detailed technical specifications for AI-powered tools and service assistants.
- Develop proof-of-concept prototypes using LangChain, MCP, RAG pipelines, and agentic workflow frameworks in Azure/Snow Flake/AWS environments - validating feasibility within rapid sprint cycles.
- Present prototype outcomes and recommendations to technical and non-technical stakeholders to support business decisions.
Application Support & Lifecycle Management
- Provide support for deployed AI applications and monitor application performance and reliability while implement continuous optimisation based on usage data and user feedback.
- Create and maintain comprehensive documentation – ETL Workflows, architecture decision records, API references, runbooks, and operational procedures.
- Support knowledge transfer to internal teams to ensure long-term maintainability beyond the contract engagement.
What You Bring
- Bachelor's/Master's degree in Computer Science Engineering.
- 3 years of full-stack engineering experience, with a minimum of 1 years focused on AI/ML and LLM application development.
- Engage stakeholders to identify manual, paper-based, or inefficient processes and evaluate high-value digitalisation opportunities.
- Advanced proficiency in Python; strong experience with LangChain, or equivalent LLM frameworks and knowledge of PowerBI to build dashboards for analytics.
- Demonstrated understanding of agentic workflows, Model Context Protocol (MCP), RAG pipelines, NLP, and generative AI.
- Proven experience developing and managing REST APIs and integrating AI services into enterprise platforms using OpenAI/Claude.
- Production deployment experience on AWS and/or Azure; familiarity with DevOps practices and containerisation.
- Proficiency with modern front-end frameworks - React preferred with experience on HTML.
- Strong stakeholder communication and ability to understand and develop front end/backend of application, define requirements, and present technical recommendations to non-technical audiences.
- Deploy automated workflows that eliminate repetitive manual effort, streamline approvals, and enhance team productivity.
- Drive adoption of digital tools through demonstrations, user training, and change management support - ensuring teams embrace and sustain new ways of working.
- Support the broader digitilisation strategy by championing continuous improvement and measurable impact across engineering processes.
