Senior Cloud Engineer (AWS)

Leatherhead
3 weeks ago
Create job alert

Senior Cloud Engineer (AWS)
British Citizens only (due to clearance)
Location: Leatherhead or Bristol
Working Pattern: 2 days on-site - Flexible hybrid working pattern with time split between the office, client sites, and working from home.
About the Role: We are seeking an experienced AWS Cloud Engineer to join a leading consultancy firm. This role involves accelerating the design and implementation of innovative cloud solutions for clients in defence, energy, and industry.
Role Overview: As a Senior Cloud Engineer, you will manage projects, taking technical ownership of custom software applications and data systems for complex STEM applications. You will work across various industries, ensuring the highest standards of development and protection for critical services and products.
Key Responsibilities:

Lead the design and deployment of complex cloud solutions on AWS.
Develop software applications and data systems from the ground up.
Manage and deliver projects, ensuring technical excellence.
Collaborate with clients to understand and meet their needs.
Implement and maintain containerized applications.
Present complex topics in an understandable way.
Utilize consultancy skills in stakeholder management and business development.Recent Projects:

Horizon scanning applications with graph databases, big datasets, and natural language processing in AWS.
Simulations of distributed autonomous systems architectures using Python, Kafka, and Azure.
Data processing applications for critical infrastructure using ASP.NET, Entity Framework, Postgres, and C#.Requirements:

Significant experience with AWS cloud solutions.
Proficiency in at least one object-oriented language (Python or C#).
Experience with containerization.
Strong interpersonal and consultancy skills.
Ability to present complex topics clearly.Preferred Qualifications:

AWS certifications.
Experience with Azure DevOps or similar.
Agile project management experience.
Database design and management (Relational or NoSQL).Benefits:

Competitive salary with yearly reviews.
25 days holiday + option to buy 5 additional days.
Flexible working arrangements.
Enhanced parental benefits.
Company pension scheme.
Professional development opportunities.
Life assurance and private healthcare.
Performance-linked bonus scheme.
Paid membership fees to professional institutions.
Cycle to work scheme and season rail ticket loan.
Additional optional benefits tailored to your needs.How to Apply: Want to find out more? Click Apply

Related Jobs

View all jobs

Senior Software Engineers

Senior Data Engineer (with ML knowledge)

Senior Data Engineer

Senior Teradata Engineer

Senior Data Engineer

Senior Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.