Senior Software Engineer

Brainpool is a fast growing AI start-up, providing custom AI services for business since 2017. Brainpool network of 500 top-level AI and Machine Learning experts supporting delivery of our projects include PhD and MSc-level scientists from top universities such as UCL, Oxford, Cambridge and Harvard. Brainpool provides companies with end-to-end AI solutions, starting from strategy development, planning all the way to implementation.

This role will involve working alongside the CTO and a team of engineers to develop cutting-edge AI solutions for client projects and internal company products. You'll contribute to key deliverables such as AI scoping programmes, PoC development, and production-ready AI systems, with a significant focus on Brainpool's LLM-powered applications like the AI Quote Generation system detailed in our recent client proposal.

Key Responsibilities

• Design and implement robust RAG (Retrieval-Augmented Generation) pipelines for processing complex document collections and technical documentation
• Develop LLM integration systems with AWS Bedrock for models like Claude and Mistral
• Create evaluation frameworks for benchmarking and improving LLM performance
• Build and optimize FastAPI-based REST endpoints with Swagger documentation for AI services
• Implement vector database solutions using technologies like Qdrant
• Contribute to containerized development and deployment environments using Docker and AWS ECS
• Participate in prompt engineering and enhancement of HyDE-based retrieval systems
• Collaborate with cross-functional teams on UI development for testing interfaces and evaluation dashboards

Requirements

• Strong experience with Python, with a focus on building production-grade AI applications
• Proven experience working with LLM frameworks such as LlamaIndex, Haystack, or LangChain
• Experience implementing RAG (Retrieval-Augmented Generation) systems with vector databases
• Solid understanding of AWS services, particularly Bedrock, ECS, S3, and CloudWatch
• Experience with Docker containerization and CI/CD pipelines
• Familiarity with REST API development using FastAPI or similar frameworks
• Knowledge of vector databases (Qdrant, Weaviate, or similar)
• Strong communication skills to interface with both technical and business stakeholders
• BSc or MSc in Computer Science, Data Science, or related STEM field

Desirable Experience

• Experience with prompt engineering and optimization for different LLM models
• Knowledge of advanced RAG techniques like HyDE (Hypothetical Document Embeddings)
• Familiarity with monitoring and evaluation frameworks for LLM applications
• Background in metrology, analytical sciences, or technical documentation processing
• Understanding of embedding models and vector search optimization