Senior MLOps / ML / AI Ops Engineer
Hybrid Working – London
Excellent Salary + Bonus + Benefits
An exciting opportunity has arisen to join a cutting-edge data and AI consultancy as a Senior MLOps / ML / AI Ops Engineer. This role is ideal for someone passionate about building scalable, secure, and innovative machine learning and Generative AI solutions—particularly involving Large Language Models and multi-agent systems.
You’ll play a key role in designing and deploying end-to-end AI architectures on AWS, guiding clients through best practices, and mentoring junior engineers. If you enjoy solving complex challenges and driving production-ready AI systems, this is an opportunity to work at the forefront of the industry.
What you’ll be doing
* Architecture & Design: Develop secure, scalable ML and GenAI architectures using AWS services such as SageMaker, EKS, Fargate, Lambda, and Step Functions. Build event-driven microservices and automate data pipelines using Airflow and dbt.
* Production Deployment: Build and maintain CI/CD pipelines for ML models and AI agent systems using GitHub Actions, Jenkins, or AWS CodePipeline. Deploy and orchestrate LLMs from platforms like Hugging Face using frameworks such as LangChain or custom agent orchestrators.
* Multi-Agent Systems: Design and manage multi-agent AI workflows, coordinating memory, authentication, conflict resolution, and secure task-handoffs between agents.
* Model Ops & Monitoring: Manage the full model lifecycle with tools like MLflow and SageMaker Model Registry. Build monitoring dashboards (CloudWatch, Prometheus, Grafana) and implement data quality checks and automated retraining.
* Security & Compliance: Apply robust security controls, credential management, vulnerability scanning, and guardrails for GenAI applications. Work with IAM, encryption, VPC design, GDPR compliance, and threat-mitigation patterns.
* Technical Leadership: Promote software engineering excellence, drive best practices, and mentor junior members of the team.
What you’ll bring
* 3+ years’ experience in MLOps / ML Engineering / AI Ops
* Strong AWS expertise—SageMaker, EKS/Fargate, Lambda, Step Functions, S3, CloudWatch
* Hands-on experience with Terraform or AWS CDK
* Proficiency in Docker and Kubernetes
* Experience delivering ML lifecycle management via MLflow (or similar)
* Background deploying LLMs and building multi-agent systems with LangChain/LangGraph or custom frameworks
* Experience developing data pipelines with Airflow or Step Functions
* Strong grounding in software engineering, testing, observability, and cost optimisation
* Experience building dashboards and performing data validation
Nice to have:
Consulting or presales background,MCP knowledge, Databricks experience, AWS certifications (ML Speciality / AI Practitioner)
Why apply?
* Join a highly specialised team working on advanced ML and GenAI delivery
* Hybrid working with a London base
* Excellent salary package, bonus, and comprehensive benefits
* Exposure to cutting-edge AI agent-based architectures and enterprise-scale AWS environments