Senior Full Stack Engineer

About Trusted:

We’re on a mission to help global organisations win more profitable business faster, through intelligently capturing and converting the trusted voice of the customer. Trusted is set to redefine Customer Advocacy Marketing with a cloud-native, real-time, and AI-powered platform. We’re building the next-generation B2B demand engine, enabling brands to connect their prospects directly with their happiest customers - creating trust at scale.

Now is an incredible time to join Trusted. Backed by £1M in pre-seed funding from one VC and 18 angel investors, we’re assembling a world-class team and gearing up to start building. Reporting to the Principal Engineer, we seek a Senior Full-Stack JavaScript Engineer to help develop our React, TypeScript, and Node.js-powered platform. You’ll be key in building scalable, high-performance applications while collaborating closely with engineering leadership and product strategists.

What you'll do:

• Develop & Maintain Full-Stack Applications – Build and optimise scalable, high-performance applications using React, TypeScript, and Node.js (We use Nest.js and Next.js). Ensure seamless interactions between the frontend and backend, delivering a highly responsive and intuitive user experience.
• Enhance API & Backend Services for AI Agents– Design, implement, and maintain secure, high-performance APIs that integrate with AI agent systems and LLMs (OpenAI, Anthropic Claude, or similar). Develop robust API endpoints to facilitate real-time AI interactions and automation workflows..
• Work with AI & LLM Tools - Implement retrieval-augmented generation (RAG) pipelines, fine- tune LLM prompts, and integrate AI-driven decision-making into the product. Experiment with vector databases (Weaviate, Pinecone, FAISS) to enhance model retrieval capabilities.
• Build and optimise UI Components - Work with Storybook and component-driven development to create a reusable, scalable design system that ensures consistency, accessibility, and responsiveness across the platform. Collaborate with the Product Lead to refine UI/UX based on real-time user feedback and behavioural analytics.
• Ensure Security, Testing & Performance Optimisation – Implement SOC 2-compliant security best practices, including data encryption, role-based access control (RBAC), and secure API authentication. To ensure reliability, develop comprehensive test coverage, including unit, integration, and end-to-end tests. Continuously optimise front and backend performance to handle increasing traffic and scale efficiently.
• Improve Deployment Pipelines & Observability – Work with DevOps to enhance CI/CD automation, infrastructure-as-code (IaC), and cloud deployments, ensuring a secure, scalable, and SOC 2-compliant environment. Implement logging, monitoring, and alerting solutions to proactively detect issues, minimise downtime, and maintain high availability.
• Collaborate with Engineering & Product Teams – Work closely with the Principal Engineer, and Product Lead to align frontend and backend architecture with product goals, scalability needs, and compliance requirements.

What we're looking for:

• Strong commercial experience in full-stack development, with expertise in React, TypeScript, and Node.js. (Ideally Nest.js and Next.js) - ideally 5+ years commercial exp
• Strong API design experience, including building and maintaining secure, efficient RESTful and or/ GraphQL APIs that integrate with LLMs, vector databases, and AI decision-making engines.
• Experience architecting multi-tenant, high-performance databases using both relational and NoSQL paradigms, including RLS and RBAC.
• Experience with vector databases (Weaviate, Pinecone, FAISS) and AI-enhanced search or recommendation systems.
• Hands-on experience with AI APIs (OpenAI, Anthropic Claude, or similar) – Ability to design and fine-tune AI-driven interactions within the product.
• Experience with cloud platforms (AWS, GCP, or Azure), including containerisation (Docker/Kubernetes), serverless architectures, and cloud-native deployments optimised for AI workloads.
• Proficiency with DevOps and CI/CD pipelines, ensuring automated deployments, monitoring, and AI model observability.
• Strong testing background, with experience writing unit, integration, and end-to-end tests to validate AI interactions, data pipelines, and real-time API calls.
• Strong problem-solving and debugging skills, with a focus on AI scalability, performance optimisation, and trustworthiness.

Nice to have:

• Experience building AI-driven applications, including LLM-powered workflows, AI agents, and RAG (retrieval-augmented generation).
• Understanding of SOC 2 compliance requirements and experience implementing secure LLM workflows, data encryption, role-based access control (RBAC), and API authentication strategies.

Why join us?

• £75,000 - £80,000 basic salary, plus meaningful equity options within a pre-seed VC backed business
• 25 days holiday, plus bank holidays
• Remote-first, high-trust environment with flexible hours
• Be an early part of a high-growth AI-driven SaaS startup backed by £1M in pre-seed funding from top investors.
• Work on cutting-edge AI-powered technologies, integrating LLMs, AI agents, and scalable full-stack applications
• Solve complex challenges in AI, scalability, and security, including retrieval-augmented generation (RAG), vector databases, and SOC 2 compliance
• Home-office budget and personal development budget

Interview Process:

Step 1 - Initial Conversation (30 mins)

A chance to connect on both sides. We’ll spend time learning about your background and career goals, and give you a clear, concise overview of our business, mission, and culture.

Step 2 - Technical Deep Dive (30 mins)

A structured discussion to explore technical alignment, architectural thinking, and how you approach problem-solving. This is also your opportunity to assess how we operate and whether we’re a good fit for your working style.

Step 3- Collaborative Pairing Session (90 mins)

A hands-on session with one of our principal engineer. Together, we’ll work through a realistic technical problem. The goal is to simulate what it’s like to collaborate day-to-day, not to test, but to explore how we think, communicate, and solve things together