Ai engineer for agentic applications

Задачи

• Design and build robust, secure APIs and backend components for AI/ML, GenAI, and agentic applications;
  Engineer agentic systems by integrating LLMs with tools, data sources, and business workflows into reliable production-grade pipelines;
  Drive systems from prototype to production, owning reliability, scalability, and operational readiness;
  Improve code quality, structure, and production readiness across the AI/ML stack;
  Debug and resolve issues across APIs, environments, and integrations;
  Act as the primary technical partner between Data Science and Engineering, Dev Ops, and Infrastructure teams;
  Support colleagues whose systems integrate with AI/ML and agentic components;
  Resolve technical ambiguity to reduce delivery friction and rework;
  Establish and evolve engineering standards for product ionising AI/ML, including testing, observability, versioning, and release management;
  Mentor and guide data scientists and engineers through code reviews and hands-on technical support;
  Champion disciplined engineering, continuous improvement, and operational excellence within Data Science.

• Degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related technical discipline, or equivalent hands-on experience;
• Exceptionally strong Python skills with knowledge of object-oriented design, clean code, SOLID, design patterns, modularity, and testability;
• Strong backend and API engineering experience, ideally with Python and FastAPI or similar;
• Hands-on experience building and operating solutions in AWS;
• Proficiency with Docker, Git Hub, and CI/CD pipelines;
• Proven ability to work across teams and drive delivery into production;
• Strong problem-solving, debugging, and performance optimisation skills;
• Solid software engineering foundations, including version control, automated testing, and monitoring;
• Nice to have:
  Experience with agentic AI systems, GenAI and LLM systems in production, MCP, MLOps pipelines, real-time or streaming systems.

• Competitive salary and company bonus scheme;
• Group pension scheme;
• Group healthcare and life assurance scheme;
• Hybrid working environment with currently three days in office;
• 25 Days annual holiday, increasing incrementally up to 30 days;
• Subsidised gym membership;
• Season ticket travel loan;
• Cycle to work scheme;
• Flexible benefits platform with additional medical cover, life assurance, dental cover, holiday, critical illness, travel insurance, and health screening;
• Extensive internal and external training.