Software Architect, Intelligent Automation

SS&C Technologies Holdings
1 year ago
Applications closed

Related Jobs

View all jobs

Associate Director, Data Science/Gen AI Lead - ER&I

Associate Director, Data Science/Gen AI Lead - ER&I

Associate Director, Data Science/Gen AI Lead - ER&I

Associate Director, Data Science/Gen AI Lead - ER&I

Associate Director, Data Science/Gen AI Lead - ER&I

Artificial Intelligence and Machine Learning Graduate

Job Description

SS&C Blue Prism

SS&C Blue Prism allows organizations to deliver transformational business value via our intelligent automation platform. We make products with one aim in mind - to improve experiences for people. By connecting people and digital workers you can use the right resource, every time, for the best customer and business outcomes. We supply enterprise-wide software that not only provides full control and governance, but also allows businesses to react fast to continuous change.

 Exceed customer expectations, stay competitive, accelerate growth.

About the Role


We now seek a highly skilledSoftware Architectto join our dynamic team. As a Software Architect, you will be responsible for designing and implementing the overall structure of our software systems. You will collaborate with cross-functional teams to ensure the successful delivery of high-quality software solutions that meet our clients' needs. The ideal candidate will have a strong background in software development, excellent problem-solving skills, and a deep understanding of software architecture principles.

The successful candidate will be a strong collaborative team player who thrives on technical challenges, applies sound judgment and enjoys working as part of an agile team.

Your Responsibilities

  • Work closely with development team leads and senior developers to guide the evolution of our software towards a scalable, reliable, highly available and maintainable architecture.
  • Identify and mitigate technical risks and issues, ensuring timely resolution
  • Work with upper management and solution architect to define the business's longer-term technical vision.
  • When in a sprint team, work closely alongside product owners, developers, QA, etc. to ensure epics/user stories are delivered to high quality and pragmatically.
  • Define prototype/reference architectures to serve as blueprints during implementation.
  • Stay up-to-date with emerging technologies and industry trends, and recommend innovative solutions to enhance our software systems.

Your Experience

We seek proven experience as a Software Architect or a similar role, with a strong background in .NET C# software development.

Scalable distributed systems and experience with several of the following:

  • In-depth knowledge of software architecture principles, design patterns, and best practices.
  • Enterprise .NET development experience (8+ years) and in-depth knowledge of .NET eco-system (commercial and open source libraries, platforms etc.)
  • Database design, ORMs, efficient data access
  • OO design, modelling of complex domains, Domain Driven Design
  • Agile development practices includeClean Code, Code Complete, TDD, Unit Testing, Continuous Integration and Continuous Delivery.

Desirable skills:

  • Experience with alternative languages, application development frameworks and technologies, e.g. Python, node.js, Ruby
  • AI/Machine Learning/Computer Vision
  • Alternative RDBMS and NoSQL data stores
  • Containerisation and orchestration
  • Experience with cloud-based technologies and microservices architecture.

EEO Statement / Non-agency Disclosure

We encourage applications from people of all backgrounds and particularly welcome applications from under-represented groups, to enable us to bring a diversity of perspectives to our thinking and conversation. It's important to us that we strive to have a workforce that is diverse in the widest sense.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.