Lead Software Engineer We are hiring a Lead Software Engineer to help architect, build and scale the core systems powering a conversational AI platform. This is a high-impact role with strong ownership across backend services, inference systems, APIs and supporting infrastructure. This role is best suited to a senior engineer who enjoys solving complex technical problems, working across distributed systems, and building reliable, scalable platforms that support real-time AI applications. While the role is full stack, it is weighted toward backend engineering, systems design and production reliability rather than UI-heavy maintenance work. About the role You will work closely with engineering, product and AI teams to design and deliver low-latency, high-throughput systems that support large language models and conversational AI products in production. You will play a key role in shaping technical direction, improving platform performance, and ensuring systems are scalable, secure and reliable as the business continues to grow. Key responsibilities Architect, build and maintain backend systems, APIs and infrastructure for a production AI platform Design low-latency, high-throughput services that support real-time LLM and NLP workloads Build and optimise REST and GraphQL APIs, event-driven services and cloud-based infrastructure Work with AWS services, Infrastructure-as-Code and modern DevOps practices Support LLM deployment, orchestration, lifecycle management and RAG-style architectures Collaborate with ML engineers, product teams and other engineers to deliver complex technical initiatives Contribute to engineering standards including testing, code review, documentation and secure development practices Influence architectural decisions and improve platform reliability, performance and cost efficiency What you will bring 7 years of professional software engineering experience Strong experience building production-grade distributed systems Solid backend engineering experience across APIs, microservices and cloud infrastructure Hands-on experience with AWS and Infrastructure-as-Code tools such as Terraform, CDK, CloudFormation or similar Experience with LLMs, NLP systems, AI/ML workloads or model orchestration in production Experience with vector databases and RAG-based architectures Strong Node.js and TypeScript experience, ideally across frameworks such as Express, Fastify, NestJS, React or Next.js Strong understanding of Git, secure development practices, OWASP, secrets management and access control Ability to write clean, tested and well-documented code Strong communication skills and the ability to work cross-functionally in a fast-moving environment Nice to have Experience with Azure or hybrid cloud environments PostgreSQL and relational data modelling experience Python experience, including FastAPI, Flask, LangChain, Pandas or NumPy Experience with Kafka, NATS, EventBridge or other event-driven architecture tools Docker and Kubernetes experience Observability experience using tools such as OpenTelemetry, CloudWatch or Grafana CI/CD and DevSecOps experience What success looks like In the first 30 days, you will build a strong understanding of the platform, architecture and deployment workflows while making your first production contribution. Over the following months, you will take ownership of critical system components, improve latency, reliability and cost efficiency, and begin influencing technical direction through architecture input and code reviews. Over 6–12 months, you will lead the design and implementation of major platform improvements and become a key technical owner within the engineering team. Benefits Join a fast-growing, innovative technology business Work on modern AI systems with real production impact High level of ownership and technical influence Strong professional growth and career development opportunities Competitive salary Flexible, remote-first working environment
