Senior MLOps Engineer

E-Solutions; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

E-Solutions in London seeks a Senior Engineer to lead teams, shape technical design, and drive ML-enabled software delivery. You will own architecture across software, data, AI/ML and cloud platforms, and mentor engineers to foster technical excellence.

Responsibilities include end-to-end development of applications and APIs, data pipelines and MLOps practices, plus deployment, monitoring and governance. You will partner with stakeholders to align priorities and deliver robust, scalable

Qualifications

• Significant enterprise software, data, AI/ML, cloud engineering experience.
• Proven technical leadership delivering complex scalable solutions.
• Experience managing engineers, mentoring talent and building high-performing teams.
• Strong architectural judgement, problem-solving and hands-on capability.
• Experience with Agile delivery, cross-functional collaboration and stakeholder management.
• Ability to translate business requirements into practical technical solutions.
• Experience evaluating and implementing emerging technologies, including AI/ML.
• Strong communication, ownership and strategic thinking.

Responsibilities

• Define technical architecture and scalable solutions across software, data, AI/ML and cloud.
• Lead end-to-end development of applications, APIs and integrations.
• Oversee data pipelines, governance and analytics platforms.
• Lead AI/ML design, integration and deployment including LLMs.
• Guide MLOps practices, model deployment and monitoring.
• Drive cloud-native architecture, CI/CD and security.
• Lead and coach engineers and drive recruitment.
• Own delivery priorities, risks and stakeholder engagement.

Skills

Leadership

Architectural Judgement

Problem Solving

Hands-on Coding

Agile Delivery

Stakeholder Management

Communication

Cloud Engineering

AI/ML

Education

Bachelor’s degree in Computer Science, Engineering, Data Science

Advanced degree in Computer Science/ML (preferred)

Tools

Azure

AWS

Kubernetes

Docker

Terraform

GitHub Actions

Azure DevOps

CI/CD

Power BI

Tableau

Snowflake

Databricks

Job description

As a member of our team, the Senior Engineer is responsible for leading teams, technical design, software development and ongoing maintenance. This individual participates in technical design processes and carries out coding tasks, ensuring that all machine learning related capabilities are delivered to a high standard.

Additionally, the Senior Engineer plays a key part in supporting and operating systems, identifying defects, leading troubleshooting activities, and facilitating code deployments to production environments.

Essential Functions

ML System Development, Support & Maintenance

• Architecture & Engineering: Define technical architecture, engineering standards and scalable solutions across software, data, AI/ML and cloud platforms.
• Software Development: Lead end-to-end application development, APIs, integrations, testing and technical quality.
• Data Engineering: Oversee data architecture, pipelines, integration, modelling, governance and analytics platforms.
• AI & Machine Learning: Lead the design, integration and deployment of AI/ML solutions, including generative AI, LLMs, intelligent automation and predictive analytics.
• AI/ML Operations: Guide model deployment, evaluation, monitoring, MLOps practices and responsible AI implementation.
• Cloud & DevOps: Drive cloud-native architecture, CI/CD, infrastructure automation, security, reliability and operational excellence.
• People Leadership: Manage, coach and develop engineers, support recruitment and performance management, and build strong technical capabilities.
• Delivery Management: Own technical delivery, priorities, risks, stakeholder engagement and engineering outcomes.
• Innovation: Evaluate emerging technologies, lead proofs of concept and promote AI-enabled engineering productivity and continuous improvement.

Technical Skills

Strong expertise in core engineering discipline, with broad knowledge across:

• Data: SQL, NoSQL, Spark, Kafka, ETL/ELT, data modelling and modern data platforms.
• AI/ML: Python, ML frameworks, LLMs, RAG, AI agents, model evaluation, MLOps and AI integration patterns.
• Cloud: Microsoft Azure, AWS, cloud-native services and distributed architectures.
• DevOps: Docker, Kubernetes, Terraform, GitHub Actions, Azure DevOps and CI/CD.
• Analytics: Power BI, Tableau and modern visualisation technologies.
• Engineering Practices: Agile, automated testing, security, observability, architecture governance and technical assurance.
• Data Platforms: Snowflake, DataBricks

Leadership & Experience

• Significant experience in enterprise software, data, AI/ML, cloud engineering or architecture.
• Proven technical leadership delivering complex, scalable solutions.
• Experience managing engineers, mentoring talent and building high-performing teams.
• Strong architectural judgement, problem-solving and hands‑on technical capability.
• Experience with Agile delivery, cross-functional collaboration and stakeholder management.
• Ability to translate business requirements into practical technical solutions.
• Experience evaluating and implementing emerging technologies, including AI and ML.
• Strong communication, ownership and strategic thinking.

Preferred Qualifications

• Experience with MLOps tools and platforms (e.g., Azure ML, Databricks)
• Knowledge of GenAI/LLMs and their application in enterprise settings
• Understanding of model monitoring, explainability, and responsible AI practices

Education:

• Required: Bachelor’s degree in Computer Science, Engineering, Data Science, or related field, or equivalent practical experience.
• Preferred: Advanced degree in Computer Science, Machine Learning, or a related technical discipline.

Language Requirement:

• Advanced English proficiency (written and spoken) required.