At a Glance
- Tasks: Design and build AI-driven systems, integrating with top AI platforms and developing scalable cloud-native solutions.
- Company: Dynamic tech company focused on innovative AI solutions in a hybrid work environment.
- Benefits: Competitive salary, flexible remote work, and opportunities for professional growth.
- Other info: Hands-on role with excellent career advancement potential in a collaborative setting.
- Why this job: Join a cutting-edge team and shape the future of AI technology in real-world applications.
- Qualifications: 8-10+ years in software engineering with strong cloud-native and AI system experience.
The predicted salary is between 80000 - 100000 € per year.
Location: London Area – Hybrid - 3 Days in a week
Note: Candidates must have the right to work in the UK independently, as visa sponsorship is not available for this role.
Seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. The role focuses on implementing agent-based workflows, integrating AI platforms, and delivering scalable cloud-native solutions.
Responsibilities
- AI Agent Engineering
- Design and implement AI agents, including:
- Retrieval (RAG)
- Orchestration workflows
- Tool/function invocation
- Policy-based routing
- Build evaluation frameworks for accuracy, latency, and reliability
- Implement observability and monitoring for agent lifecycle
- AI Platform Integration
- Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models)
- Build abstraction layers to support multi-model and multi-provider architectures
- Optimize model usage for performance, cost, and latency
- Cloud-Native Development
- Develop scalable services using:
- Microservices architecture
- Containers (Docker, Kubernetes)
- Serverless and event-driven patterns
- Implement CI/CD pipelines and infrastructure as code (e.g., Terraform, Helm)
- Ensure production readiness, logging, monitoring, and fault tolerance
- Application Development
- Build and deploy AI-powered applications aligned to business workflows
- Integrate AI systems into existing enterprise platforms and APIs
- Develop backend services and APIs supporting agent workflows
- Testing & Performance
- Define and execute test strategies for AI systems
- Measure system performance (latency, throughput, accuracy, cost)
- Debug and optimize production systems
Required Skills & Experience
- 8–10+ years of software engineering experience
- Strong experience with cloud-native systems (APIs, microservices, containers, serverless)
- Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration)
- Proficiency in Python, Java, or similar backend languages
- Experience with:
- CI/CD pipelines
- Infrastructure as code
- Monitoring and observability tools
- Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar)
Preferred Experience
- Experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI)
- Experience designing multi-agent or distributed AI systems
- Familiarity with enterprise-scale system integration
- Experience optimizing AI workloads for cost and performance
Scope & Expectations
- 100% hands-on engineering role (no people management)
- Deliver production-quality code and deployments
- Work within existing architecture and engineering standards
- Collaborate with client and internal engineering teams as needed
- Participate in technical design discussions (implementation-focused)
Remote C# Engineer employer: Soho Square Solutions
As a leading employer in the tech industry, we offer a dynamic and inclusive work culture that fosters innovation and collaboration. Our hybrid working model allows for flexibility while ensuring that our engineers are at the forefront of cutting-edge AI technology, with ample opportunities for professional growth and development. Join us in London to be part of a team that values creativity and empowers you to make a meaningful impact in the world of AI-driven solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Remote C# Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections on LinkedIn or attend industry meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and cloud-native development. This gives potential employers a taste of what you can do beyond just your CV.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. We recommend using platforms like LeetCode or HackerRank to sharpen your skills and boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect with us directly.
We think you need these skills to ace Remote C# Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of AI Engineer. Highlight your experience with cloud-native systems, AI platforms, and any relevant projects that showcase your skills in building and deploying AI-driven solutions.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI engineering and how your background aligns with our needs. Be specific about your hands-on experience and how you can contribute to our team.
Showcase Your Projects:If you've worked on any AI or cloud-native projects, make sure to include them in your application. We love seeing real-world examples of your work, especially if they demonstrate your ability to design and implement scalable solutions.
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 gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Soho Square Solutions
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially cloud-native systems and AI platforms. Brush up on your knowledge of microservices, containers, and CI/CD pipelines, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly around AI agent engineering and system integration. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight how you tackled complex problems.
✨Demonstrate Your Hands-On Experience
Since this is a 100% hands-on role, be ready to share examples of your past projects where you’ve built and deployed AI-driven systems. Talk about your experience with tools like Docker, Kubernetes, and any agent frameworks you’ve used, as this will show you can hit the ground running.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s current AI initiatives and their engineering practices. This not only shows your interest but also helps you gauge if the company culture aligns with your values and work style.
