ai engineer for agentic applications

Argus is an independent provider of market intelligence for global energy and commodity markets. It delivers price assessments, news, analytics, consulting services, data science tools, and industry conferences, helping companies, trading firms, and governments make decisions, manage risk, facilitate trading, and plan for the long term.

• 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, DevOps, 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 productionising 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, GitHub, 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.