At a Glance
- Tasks: Design and deploy AI-driven systems in a hands-on engineering role.
- Company: Join a global leader in digital, cloud, and security services.
- Benefits: Enjoy a hybrid work model, competitive salary, and professional growth opportunities.
- Other info: Collaborate with experienced teams in a dynamic, execution-driven environment.
- Why this job: Build impactful AI systems that drive real business workflows.
- Qualifications: 8-10 years of software engineering experience with AI/LLM systems.
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 in London employer: LinkedIn
TekWissen Group is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. As an AI Native Software Engineer, you will have the opportunity to work on cutting-edge AI systems within a supportive environment that prioritises employee growth and development. With a hybrid work model and a focus on hands-on engineering, you'll be part of a team that values your expertise while providing access to modern technologies and impactful projects.
StudySmarter Expert Advice🤫
We think this is how you could land AI Native Software Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with AI and cloud technologies. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI systems and cloud-native applications. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding AI architectures. Practice common interview questions related to AI and cloud development to boost your confidence and impress the interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and take the initiative to connect directly with us.
We think you need these skills to ace AI Native Software Engineer in London
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 that showcase your skills in building production-grade applications.
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. Don’t forget to mention specific technologies or frameworks you’ve worked with that align with the job description.
Showcase Your Technical Skills:In your application, be sure to highlight your technical skills, especially in Python, Java, and any experience with CI/CD pipelines or cloud services. We want to see how you can contribute to our team right from the get-go!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at LinkedIn
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI systems, especially agent-based architectures and RAG pipelines. Be ready to discuss your hands-on experience with AI/LLM-based systems and how you've tackled challenges in production environments.
✨Showcase Your Cloud-Native Skills
Prepare to talk about your experience with cloud-native development, including APIs, microservices, and serverless architectures. Have examples ready that demonstrate how you've built scalable solutions and optimised performance in the cloud.
✨Demonstrate Problem-Solving Prowess
Expect technical questions that assess your problem-solving skills. Think of complex scenarios you've faced in previous roles and how you approached them. Highlight your ability to collaborate with teams to find effective solutions.
✨Communicate Clearly
Strong communication is key, especially when discussing technical concepts. Practice explaining your past projects and technical decisions in a way that's easy to understand. This will help you connect with the interviewers and showcase your expertise.
