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About the Role

This role bridges the gap between AI/ML development and real-world application, focusing on productionizing Generative AI and agentic systems. You will build APIs, tools, and workflows to ensure AI/ML solutions are reliable, scalable, and performant in production environments. As a key partner to Engineering, DevOps, and Infrastructure teams, you will own the technical journey of bringing AI/ML systems live, setting standards for production readiness and mentoring colleagues.

Responsibilities

• 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 production-grade pipelines.
• Drive systems from prototype to production, ensuring 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 to ensure rapid response times and minimal disruption.
• Act as the technical partner between Data Science and Engineering, DevOps, and Infrastructure teams for live deployment.
• Advise and support colleagues whose systems integrate with AI/ML and agentic components.
• Proactively resolve technical ambiguity to reduce delivery friction and rework.
• Establish and evolve engineering standards for productionizing AI/ML, including testing, observability, versioning, and release management.
• Mentor and guide data scientists and engineers through code reviews and technical support.
• Champion disciplined engineering, continuous improvement, and operational excellence within Data Science.

Requirements

• Exceptionally strong Python programming skills with a deep grasp of object-oriented design, clean code, and core software engineering principles.
• Strong backend / API engineering experience, ideally in Python (e.g. FastAPI, or similar).
• Hands-on experience building and operating solutions in AWS environments.
• Proficiency with Docker, GitHub, and CI/CD pipelines.
• Proven ability to partner with and work across teams to drive delivery into production.
• Strong problem-solving, debugging, and performance optimisation skills.
• Solid software engineering foundations, including version control, automated testing, and monitoring.
• Experience building or productionising agentic AI systems (tool use, orchestration, multi-step reasoning, or agent frameworks).
• Experience with GenAI / LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency optimisation).
• Exposure to MCP (Model Context Protocol) and tool-based / function-calling architectures.
• Experience deploying and operating machine learning models / MLOps pipelines (model serving, monitoring, retraining workflows).
• Experience with real-time / streaming systems.

Skills

• Python
• Object-Oriented Design
• Clean Code
• Software Engineering Principles
• Backend Engineering
• API Engineering
• FastAPI
• AWS
• Docker
• GitHub
• CI/CD
• Problem-Solving
• Debugging
• Performance Optimisation
• Version Control
• Automated Testing
• Monitoring
• Agentic AI Systems
• GenAI
• LLM Systems
• RAG
• Prompt Orchestration
• Model Evaluation
• Guardrails
• Cost Optimisation
• Latency Optimisation
• MCP
• Function-Calling Architectures
• MLOps
• Model Serving
• Model Monitoring
• Retraining Workflows
• Real-time Systems
• Streaming Systems

Location

• Hybrid

Work Type

• Hybrid

Experience Level

• Senior

Education Level

• Degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or related technical discipline, or equivalent hands-on experience.
• MSc or PhD welcome but not essential.

Benefits

• Competitive salary
• Company bonus scheme
• Group pension scheme
• Group healthcare
• Life assurance scheme
• 25 days annual holiday with incremental increase up to 30 days
• Subsidised gym membership
• Season ticket travel loan
• Cycle to work scheme
• Flexible benefits platform
• Extensive internal and external training

About the Company

• Our rapidly growing, award-winning business offers a dynamic environment for talented, entrepreneurial professionals to achieve results and grow their careers.
• Argus recognizes and rewards successful performance and as an Investor in People, we promote professional development and retain a high-performing team committed to building our success.