Senior Engineer

We are seeking a highly motivated Senior Engineer to lead the design, development, and optimisation of intelligent systems that power our next-generation applications. This is an exciting opportunity to join a growing team, working in a flexible and innovative environment to deliver world-class AI solutions that drive business value. Responsibilities will include: Architect and optimize AI-driven systems, ensuring scalability and performance. Implement vector/graph database solutions and RAG techniques for information storage and retrieval. Develop agentic reasoning workflows using frameworks like LangChain or LlamaIndex. Lead the full AI lifecycle: data ingestion, embedding, extraction, synthesis, prompt engineering, and workflow orchestration. Deploy, monitor, and maintain models in Docker-based, containerized environments. Collaborate with cross-functional teams to align AI capabilities with business goals. Contribute to internal knowledge sharing and mentor junior engineers. Skills and experience: Required: Proven expertise in utilizing Python-based frameworks such as FastAPI for API development, Celery for task management, and Postgres for database solutions. Experience with vector and graph databases, and RAG-based architectures. Experience of with agentic frameworks and orchestration frameworks such as LangChain or LlamaIndex. Solid understanding of LLMs, embeddings, and prompt engineering. Highly Desirable: Experience designing multi-agent systems or autonomous workflows. Hands-on experience with Docker and deploying containerised, cloud-native tools. Experience with advanced retrieval-augmented generation techniques, including: TAG (Tool-Augmented Generation) – integrating external tools to enhance generation capabilities. CAG (Context-Aware Generation) – leveraging dynamic context to improve relevance and coherence. GraphRAG (Graph-Augmented Retrieval-Augmented Generation) – utilizing graph-based structures to enrich retrieval and reasoning. This will include the competencies Stakeholder engagement: Works with cross-functional teams to align AI-driven systems and capabilities with business goals and ensure solutions deliver meaningful business value. Collaboration and teamwork: Collaborates within a growing engineering team, contributing to shared delivery of AI solutions and supporting others through knowledge sharing and mentoring of junior engineers. Adapting to change: Operates in a flexible and innovative environment, adjusting approaches across the AI lifecycle as systems, tools, and requirements evolve. Continuous Improvement: Designs, optimises, monitors, and maintains AI-driven systems to ensure ongoing performance, scalability, and reliability across deployed solutions. Innovation: Develops and implements advanced AI architectures, including agentic workflows, vector and graph databases, and retrieval-augmented generation techniques to support next-generation applications. Resilience: Manages the end-to-end AI lifecycle, including deployment, monitoring, and maintenance of containerised models, maintaining stability and performance in production environments. Future Focused: Builds cloud-native, scalable AI systems using modern frameworks and architectures to support the long-term evolution of next-generation applications.