Python Developer

Direct Responsibilities

• To work as a developer in the Generative AI team which is split between multiple locations – London, Paris and Lisbon 

• Participate in an agile based software development lifecycle including technical analysis, documentation, development, testing, code reviews and working with infrastructure teams as needed. 

• Supporting the Generative AI platform service and ensuring its availability and continuous improvement to new language models and techniques and use cases. 

• Proactively manage all issue facing the team – technical, functional or organizational

Technical & Behavioral Competencies

Python Engineering.

• Strong development expertise (3 years Java/C++ and 5+ years Python), with the ability to build scalable, maintainable, production-grade systems.

• Combined experience is fine as well Deep understanding of Data Structures & Algorithms and their appropriate use cases.

• Ability to analyze and optimize solutions using Time and Space Complexity (Big-O) principles.
• Experience with Concurrency and Parallel Processing using Multithreading, Multiprocessing, Async Programming, and synchronization mechanisms
• Ability to solve complex engineering problems involving nested data structures, large-scale data processing, and system performance bottlenecks.

API & Platform Engineering

• Design and build secure, scalable, enterprise-grade APIs (using Fast API or Flask is a plus).

• Strong understanding of RESTful architecture, API lifecycle management, versioning, authentication, authorization, and API security best practices.

• Knowledge of performance optimization techniques including caching, asynchronous processing, load management, and resilience patterns.

• Familiarity with supporting technologies such as Redis, Kafka, containers, and cloud-native deployment patterns.

LLM Engineering

• Strong understanding of LLM fundamentals including Transformers, Attention Mechanisms, Embeddings, BERT, GPT, and modern foundation model architectures.
• Ability to architect enterprise-scale AI platforms with governance, observability, security, scalability, and banking-grade operational controls.
• Ability to design LLM orchestration frameworks using LangGraph (or Google ADK or CrewAI), LangChain, LlamaIndex (optional), agent workflows, tool integration, and state management.
• Experience deploying and optimizing inference platforms using technologies such as vLLM, TensorRT & KV caching or similar inference servers (e.g. slang )
• Good to have:
  • Design and implementation of enterprise Retrieval-Augmented Generation (RAG) systems
    • Deep understanding of search technologies and retrieval trade-offs(HNSW, BM25, etc )