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: Hybrid work, competitive salary, and hands-on engineering experience.
- Other info: Dynamic role with no people management, focusing on technical excellence.
- Why this job: Build impactful AI systems and collaborate with top engineering teams.
- Qualifications: 8-10 years of software engineering experience and AI system deployment.
The predicted salary is between 80000 - 100000 € per year.
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
Software Developer (AI Developer) employer: TekWissen UK
At TekWissen Group, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London-based team thrives in a hybrid environment, where employees are empowered to grow their skills in cutting-edge AI technologies while working on impactful projects that shape the future of enterprise solutions. With a strong commitment to diversity and employee development, we provide ample opportunities for professional growth and a supportive atmosphere that values every team member's contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Software Developer (AI Developer)
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or tech conferences. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and cloud-native development. Having tangible examples of your work can really set you apart when chatting with potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding AI systems. Practice common algorithms and system design questions. We recommend using platforms like LeetCode or HackerRank to get in the zone.
✨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 about their job search!
We think you need these skills to ace Software Developer (AI Developer)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of AI Native Software Engineer. 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 hands-on engineering role. Don’t forget to mention specific technologies or frameworks you’ve worked with.
Showcase Your Projects:If you've worked on any AI-driven projects or have experience with agent-based architectures, make sure to include them in your application. We love seeing real examples of your work, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at TekWissen UK
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, Java, and cloud-native systems. Brush up on your knowledge of AI platforms and frameworks such as OpenAI and LangGraph, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've designed and deployed AI-driven systems. Highlight your hands-on experience with production systems and be ready to explain your role in optimising performance and ensuring reliability.
✨Understand the Business Impact
Be ready to articulate how your work contributes to real business workflows. Employers want to see that you can connect technical solutions to business outcomes, so think about examples where your engineering efforts led to measurable improvements.
✨Practice Problem-Solving
Expect technical questions that assess your problem-solving skills. Practice coding challenges or system design scenarios related to AI and cloud infrastructure. This will help you demonstrate your technical judgement in complex environments.
