6mo ago

Senior Software Engineer

United Kingdom·LondonFull-timesenior

Software EngineerSoftware Engineering

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Quick Summary

Key Responsibilities

Design and develop scalable backend systems and APIs using Python. Build, fine-tune, and deploy applications powered by LLMs for use cases such as chatbots, content generation, summarization,

Requirements Summary

Design and develop scalable backend systems and APIs using Python. Build, fine-tune, and deploy applications powered by LLMs for use cases such as chatbots, content generation, summarization,

Technical Tools

Software EngineerSoftware Engineering

Requirements

~1 min read

6–12 years of professional software engineering experience, with a strong focus on Python.
Proven experience building and deploying production-grade systems.
Hands-on experience working with LLMs (e.g., GPT-based models, open-source LLMs) and frameworks like LangChain, LlamaIndex, or similar.
Strong understanding of RESTful APIs, microservices architecture, and distributed systems.
Experience with cloud platforms such as AWS, GCP, or Azure.
Familiarity with databases (SQL/NoSQL) and data processing pipelines.
Solid understanding of software development best practices, including version control, CI/CD, and testing.

Experience with model fine-tuning, prompt engineering, and evaluation techniques.
Knowledge of vector databases and embeddings (e.g., FAISS, Pinecone, Weaviate).
Exposure to containerization and orchestration tools like Docker and Kubernetes.
Background in machine learning or data science is a plus.

Responsibilities

~1 min read

→ Design and develop scalable backend systems and APIs using Python.
→ Build, fine-tune, and deploy applications powered by LLMs for use cases such as chatbots, content generation, summarization, and semantic search.
→ Integrate third-party LLM APIs and/or open-source models into production systems.
→ Optimize model performance, latency, and cost efficiency in real-time applications.
→ Develop robust data pipelines for preprocessing, training, and inference workflows.
→ Ensure high-quality code through testing, code reviews, and adherence to best practices.
→ Collaborate with cross-functional teams to translate business requirements into technical solutions.
→ Stay up to date with advancements in AI/ML, especially in the LLM ecosystem, and evaluate new tools and frameworks.
→ Mentor junior engineers and contribute to technical leadership within the team.