Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI - Reply

ZipRecruiter; City Of London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A data analytics firm in the City of London is looking for a Senior MLOps / Machine Learning Engineer. In this role, you will architect and deploy ML and GenAI solutions while mentoring junior engineers. Key responsibilities include leading workshops on scalable ML systems, constructing AI agent workflows, and managing CI/CD pipelines. Candidates should have a degree in a relevant field and significant experience in MLOps and Python development.

Qualifications

• 3+ years in MLOps/ML Engineering experience.
• 5+ years in Python software development or data science.
• Hands-on experience deploying LLMs and building AI agents.

Responsibilities

• Lead solution workshops to design scalable ML systems on AWS.
• Build CI/CD pipelines for deploying ML and GenAI models.
• Deploy LLMs and construct AI agent workflows.

Skills

MLOps experience

Python software development

SageMaker

AWS services

Terraform

Docker

Kubernetes

Data pipelines

Education

University degree in Computer Science or related field

Tools

MLflow

GitHub Actions

AWS CodePipeline

Airflow

Grafana

Job description

Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI

About Data Reply: Data Reply is the Reply Group company offering a broad range of analytics and data processing services. We operate across different industries and business functions, working directly with executive level professionals, enabling them to achieve meaningful outcomes through effective use of data. We help clients build their data strategy and map the right technologies to meet business needs, offering bespoke solutions and in-house training to realise the full value of big data solutions. www.data.reply.com

Role Overview

As a Senior MLOps / ML Engineer at Data Reply, you will take ownership of architecting and deploying ML and GenAI solutions. You’ll be hands-on at every stage—from proof-of-concept through production—and you’ll help mentor junior AI engineers. A particular focus will be on deploying large models (LLMs) and AI agents at scale, integrating them with enterprise workflows, and ensuring repeatable, cost-efficient AWS architectures.

Responsibilities

• Leading solution workshops to design scalable ML systems on AWS using services like VPC, IAM, SageMaker Studio, Lambda, and EKS
• Build CI/CD pipelines using GitHub Actions, Jenkins, and AWS CodePipeline for deploying traditional ML, GenAI models, and AI agents
• Deploy LLMs (e.g., via Huggingface) and construct AI agent workflows using tools like LangChain, LangGraph, and custom orchestrators
• Help reduce cloud costs with GPU acceleration, auto-scaling, and spot instances
• Implement model lifecycle tools (MLflow, SageMaker Registry), performance dashboards, alerts, and automated retraining pipelines
• Connect ML models to client systems using APIs, Kafka, and build agent workflows with vector databases (Pinecone, Weaviate)
• Enforce secure, compliant, and ethical practices—VPC design, IAM policies, data encryption, and adherence to GDPR
• Act as a trusted advisor and mentor, presenting technical solutions, managing expectations, and guiding junior team members

About the candidates

• University degree in Computer Science, Mathematics or in a directly related field (2.1 min grade)
• 3+ years in MLOps/ML Engineering experience, plus 5+ years in Python software development or data science
• Skilled in SageMaker (training, endpoints, pipelines), Lambda, Step Functions, S3, and CloudWatch
• Proficiency with Terraform or AWS CDK, Docker, and Kubernetes (EKS/Fargate)
• Experienced with MLflow (or alternatives), GitHub Actions, Jenkins, AWS CodePipeline, and automated testing
• Hands-on experience deploying LLMs and building AI agents using LangChain or custom frameworks
• Strong background in building data pipelines with Airflow/dbt and managing features via Feast or similar tools
• Experience building dashboards with CloudWatch/Prometheus/Grafana and implementing data validation with Great Expectations
• Beneficial exposure to consulting/presales, MCP deployment, Databricks, and AWS ML Specialty certification

Reply is an Equal Opportunities Employer and committed to embracing diversity in the workplace. We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type regardless of race, color, religion, sex, national origin, age, disability, marital status or parental status or any other characteristic protected by law.

Reply is committed to making sure that our selection methods are fair to everyone. To help you during the recruitment process, please let us know of any reasonable adjustments you may need.