Senior Fullstack Engineer

We are seeking a Senior Full-Stack Engineer to design and build an AI-driven conversational platform. The role involves architecting scalable systems that integrate multiple LLM providers, support real-time interactions, handle complex state management, and ensure performance, observability, and security across the stack. This position requires a deep understanding of modern web architectures, cloud-native deployments, and AI/LLM integration patterns.


Responsibilities:

  • Implement advanced chat session management, including context persistence, token optimisation, and retrieval augmented generation (RAG).
  • Design and optimise high-throughput APIs (REST, GraphQL, and WebSockets/SSE) with rate limiting and fault tolerance.
  • Integrate token metering, analytics, and usage-based billing systems.
  • Develop a secure, multi-tenant user management system with granular authentication/authorisation.
  • Leverage event-driven architectures (Kafka, Pub/Sub, or equivalent) for real-time processing and monitoring.
  • Optimise database schemas and queries (PostgreSQL, pgvector, Supabase) for low-latency chat history retrieval.
  • Implement vector search and RAG pipelines using Pinecone, Weaviate, or pgvector for knowledge grounding.
  • Ensure cloud-native scalability with Docker/Kubernetes, CI/CD pipelines, and IaC (Terraform, Pulumi).
  • Set up observability (distributed tracing, structured logging, metrics, error tracking) for debugging and performance monitoring.
  • Apply AI safety and guardrails (moderation APIs, prompt filtering, structured outputs).
  • Stay ahead of AI ecosystem developments and propose new integrations.


Requirements:

  • Backend Engineering: Node.js/Deno + TypeScript, event-driven design, API performance optimisation.
  • Frontend Development: React/Next.js (SSR, streaming responses, optimistic UI updates).
  • Databases: PostgreSQL + vector extensions (pgvector), Redis/Valkey for caching and pub/sub.
  • Cloud & Infra: AWS/GCP/Azure, Kubernetes, serverless compute (Lambda/Cloud Functions), load balancing.
  • Real-time Systems: WebSockets, Server-Sent Events, or WebRTC for interactive chat.
  • Security: OAuth2, JWT, token expiration/refresh strategies, encryption at rest and in transit.
  • Testing and Quality: Unit/integration/e2e testing frameworks, contract testing for APIs.


Nice-to-Have Skills:

  • Experience with LangChain, LlamaIndex, or custom orchestration engines.
  • Knowledge of embeddings, vector databases, and hybrid search techniques.
  • Familiarity with streaming LLM APIs and fine-tuning workflows.
  • Background in distributed systems, CAP theorem trade-offs, and scaling stateful apps.
  • Experience with observability stacks (OpenTelemetry, Grafana, Prometheus).
  • Understanding of payment and billing systems (Stripe, usage-based pricing).
  • Prior work on multi-tenant SaaS platforms.


Qualifications:

  • 5-7 years of professional experience in full-stack or platform engineering.
  • Proven experience delivering production-grade distributed systems.
  • Strong understanding of LLM APIs and AI/ML system integrations.
  • Bachelor's/Master's in Computer Science or equivalent practical experience from a pedigree background.
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