At a Glance
- Tasks: Design and deploy AI-driven systems in complex enterprise environments.
- Company: Join a global leader in digital, cloud, and security services.
- Benefits: Enjoy a hybrid work model with competitive pay and growth opportunities.
- Other info: Collaborate with experienced teams in a dynamic, hands-on role.
- Why this job: Make a real impact by building enterprise-grade AI systems.
- Qualifications: 8-10 years of software engineering experience with AI system deployment.
The predicted salary is between 70000 - 90000 € per year.
Overview:
TekWissen Group is a workforce management provider throughout the UK, Europe and many other countries in the world. The client below is a global professional services company with leading capabilities in digital, cloud, and security. Combining unmatched experience and specialized skills across more than 40 industries.
Role: AI Native Software Engineer
Location: London, UK
Work type: Hybrid
Duration: 6 Months
Job Summary:
- We are seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within complex enterprise environments.
- In this role, you will focus on agent-based architectures, AI platform integration, and cloud-native development, delivering scalable, reliable solutions that power real business workflows.
- This is a 100% hands-on engineering role, ideal for a senior technologist who thrives at the intersection of AI systems, software engineering, and cloud infrastructure.
Key Responsibilities:
Core Duties
- Design, implement, and maintain AI agent workflows, including retrieval-augmented generation (RAG), orchestration, tool/function invocation, and policy-based routing.
- Build cloud-native backend services and APIs to support AI-driven applications and enterprise integrations.
- Implement evaluation, monitoring, and observability frameworks to ensure accuracy, latency, reliability, and system health across AI agent lifecycles.
- Optimize AI and system performance across cost, scalability, and latency dimensions in production environments.
Deliverables or Project Scope
- Production-ready AI-powered applications aligned to defined business workflows and enterprise standards.
- Scalable multi-model and multi-provider AI architectures, including abstraction layers for provider flexibility.
- Fully deployed cloud-native services using microservices, containers, and serverless or event-driven patterns.
- Robust CI/CD pipelines, infrastructure-as-code implementations, logging, monitoring, and fault-tolerant deployments.
Collaboration Tools or Platforms
- Microsoft Office (Excel, Word, Outlook, Teams).
- AI Platforms Models: OpenAI, Anthropic (Claude), Google Vertex AI, and select open-source models.
- Agent Orchestration Frameworks: LangGraph, AutoGen, CrewAI (or similar).
- Cloud DevOps Tooling: Docker, Kubernetes, Terraform, Helm, CI/CD pipelines.
- Enterprise Integration: APIs, enterprise platforms, monitoring and observability tools.
Why You’ll Love This Role
- Build real, enterprise-grade AI systems that move beyond experimentation into production.
- Remain deeply technical in a 100% hands-on engineering role with no people-management responsibilities.
- Work with modern AI platforms, multi-model architectures, and cloud-native technologies.
- Focus on high-impact delivery with clear scope, measurable outcomes, and implementation ownership.
- Collaborate with experienced engineering teams in an execution-driven environment.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field or equivalent practical experience.
- 8–10+ years of professional software engineering experience with ownership of production systems.
- 3+ years of hands-on experience building and deploying AI/LLM-based systems in production (agents, RAG pipelines, orchestration).
- Strong experience designing and delivering cloud-native systems, including APIs, microservices, containers, and serverless or event-driven architectures.
- Proficiency in Python, Java, or comparable backend languages.
- Hands-on experience with CI/CD pipelines, infrastructure as code, and monitoring or observability tools.
- Proven ability to deliver production-quality code, including testing, debugging, performance tuning, and operational readiness.
Preferred Qualifications
- Experience with agent frameworks such as LangGraph, AutoGen, CrewAI, or similar.
- Experience designing multi-agent or distributed AI systems.
- Familiarity with multi-model and multi-provider AI architectures.
- Experience integrating AI solutions into enterprise-scale systems or platforms.
- Demonstrated experience optimizing AI workloads for cost, performance, and latency.
Additional Information / Requirements
- This is a 100% hands-on engineering role with no people-management responsibilities.
- Strong problem-solving skills and technical judgment in complex enterprise environments.
- Ability to collaborate effectively with internal and client engineering teams.
- Comfortable working within existing architecture standards, security requirements, and engineering best practices.
- Strong written and verbal communication skills for technical documentation and design discussions.
TekWissen® Group is an equal opportunity employer supporting workforce diversity.
AI Native Software Engineer employer: TekWissen UK
At TekWissen Group, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As an AI Native Software Engineer in London, you'll enjoy the benefits of a hybrid work model, opportunities for professional growth, and the chance to work with cutting-edge technologies in a supportive environment that values diversity and inclusion.
StudySmarter Expert Advice🤫
We think this is how you could land AI Native Software Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at your dream company. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to AI and cloud-native development. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills. Remember, confidence is key, so the more you practise, the better you'll feel!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented folks like you. Plus, it’s a great way to ensure your application gets seen by the right people. So, what are you waiting for? Get applying!
We think you need these skills to ace AI Native Software Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Native Software Engineer role. Highlight your experience with AI systems, cloud-native development, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for this role. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects:If you've worked on any AI-driven systems or cloud-native applications, make sure to showcase them in your application. Include links to your GitHub or any live demos if possible. We’re keen to see your hands-on experience!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you’re genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at TekWissen UK
✨Know Your AI Inside Out
Make sure you brush up on the latest AI technologies and frameworks mentioned in the job description, like LangGraph or OpenAI. Be ready to discuss your hands-on experience with AI systems and how you've implemented them in production environments.
✨Showcase Your Cloud-Native Skills
Prepare to talk about your experience with cloud-native development, especially using tools like Docker and Kubernetes. Have examples ready that demonstrate how you've built scalable backend services and APIs that support AI-driven applications.
✨Demonstrate Problem-Solving Prowess
Expect technical questions that test your problem-solving skills in complex enterprise environments. Think of specific challenges you've faced in previous roles and how you overcame them, particularly in relation to AI performance optimisation and system health.
✨Communicate Clearly and Effectively
Since strong communication skills are essential, practice explaining your technical projects in simple terms. Be prepared to discuss your design decisions and how they align with business workflows, ensuring you can articulate your thought process clearly.
