National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Akkodis | System Architect

Akkodis
Stevenage
6 months ago
Applications closed

Akkodis is a global leader in engineering, technology, and R&D, harnessing the power of connected data to drive digital transformation and innovation for a smarter, more sustainable future. As part of the Adecco Group, Akkodis combines the expertise of AKKA and Modis, with over 50,000 engineers and digital specialists across 30 countries in North America, EMEA, and APAC. Our teams bring extensive cross-sector knowledge in critical technology areas such as mobility, software services, robotics, simulations, cybersecurity, AI, and data analytics, enabling clients to tackle complex challenges in today’s rapidly evolving markets.


With a comprehensive solution portfolio across four service lines—Consulting, Solutions, Talents, and Academy—Akkodis supports clients from concept through to full-scale deployment and optimisation. Our diverse offerings help organisations rethink product development, accelerate productivity, reduce time-to-market, and prepare for the future. At Akkodis, you’ll join a dynamic environment that values continuous learning and global collaboration, where you can make a meaningful impact through innovative projects that shape the future of technology.


Scope:

Akkodis is launching a new technical delivery team to drive a UK national program in collaboration with key partners, designed to transform and future-proof the central government’s workforce. By leveraging cutting-edge technology, strategic partnerships, and a comprehensive SaaS-based platform, this program will create an advanced, candidate-centric experience tailored to meet tomorrow’s public sector skill demands.


This high-impact initiative offers a unique opportunity to join a team dedicated to building a scalable, data-driven recruitment ecosystem. Through redesigning, building, and rolling out a sophisticated Big Data system, our diverse roles span across architecture, project management, data analytics, development, and technical support, giving you the chance to shape a dynamic, next-gen digital infrastructure.


You’ll be integral to our mission of crafting a seamless, powerful platform that empowers the public sector with the talent to navigate an evolving digital landscape.

As a System Architect, you will lead the design and implementation of complex system integrations in high-availability environments. This role will require a deep understanding of system integration, API development, and large-scale project leadership, with particular expertise in integration into Applicant Tracking Systems (ATS).


Role:

  • Design and document scalable, resilient, and high-performing system architectures.
  • Lead the integration of complex systems, ensuring seamless interoperability between disparate platforms, including ATS.
  • Define, implement, and manage APIs for secure communication between systems.
  • Design and implement architectures supporting high availability and fault tolerance.
  • Collaborate with stakeholders to translate business requirements into technical designs.
  • Troubleshoot and resolve system integration issues to minimise operational impact.
  • Provide technical mentorship to development teams, fostering best practices.
  • Ensure solutions meet compliance, security, and performance standards.
  • Recommend innovative approaches to improve system efficiency and integration.


Responsibilities:

  • System Architecture Design: Develop scalable and robust architectures.
  • Integration Leadership: Manage system integrations and ensure interoperability.
  • API Management: Oversee API design and security protocols.
  • High-Availability Solutions: Minimise downtime through resilient architectures.
  • Stakeholder Collaboration: Translate business needs into technical solutions.
  • Problem Resolution: Address and resolve integration challenges.
  • Technical Leadership: Mentor teams on system integration best practices.
  • Compliance and Standards: Meet industry security and performance benchmarks.
  • Continuous Improvement: Introduce advanced technologies and methodologies.


Required Skills:

  • Expertise in system integration patterns and middleware technologies.
  • Proficiency in RESTful and SOAP APIs, including API management platforms.
  • Experience with AWS cloud platforms and architectures.
  • Strong programming skills in Java, Python, or Node.js.
  • Knowledge of security protocols like OAuth, SAML, and JWT.
  • Familiarity with tools like Adobe Experience Manager, Sprinklr, and Twilio.
  • Understanding of Microsoft VDI and 365 administration.


Required Experience:

  • Proven experience in system integration and API development.
  • Leadership in large-scale integrations within high-availability environments.
  • Familiarity with ATS or similar HR systems.
  • Familiarity with microservices architecture and containerisation tools (e.g., Docker, Kubernetes).
  • Experience with event-driven architecture and message queuing systems (e.g., Kafka, RabbitMQ).
  • Hands-on knowledge of CI/CD pipelines and DevOps practices.
  • Expertise with monitoring and logging tools like CloudWatch.
National AI Awards 2025

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.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.