Full Stack AI Engineer

Build production services using Python, FastAPI and Pydantic models.  

Develop APIs and backend workflows that support AI-enabled document and contract intelligence.  

Work with PostgreSQL, SQLAlchemy and Alembic to model, migrate and operate reliable data layers.  

Build and maintain asynchronous job systems, including queue processing, retries, idempotency, dead-letter handling, cancellation, progress tracking and failure recovery.  

Use Redis for caching, transient state, job status and coordination, with sensible reliability patterns such as timeouts, circuit breakers and graceful degradation.  

Build React and TypeScript interfaces that consume backend services cleanly and provide users with transparent job states, useful error handling and polished interaction patterns.  

Use TanStack Query for server state, including query key factories, cache invalidation, optimistic updates and polling patterns for long-running AI jobs.  

Support document-heavy workflows, including ingestion, retrieval, structured extraction, redlining, rich text editing and AI-assisted review.  

Build features that respect enterprise security expectations, including authentication, authorisation, secure data handling and auditability.  

Operate within Azure-based environments, including services such as Blob Storage, Key Vault, managed databases, Redis and containerised deployments.  

Instrument production systems using Application Insights or equivalent observability tooling.  

Use AI coding tools to accelerate implementation, debugging, refactoring, testing and documentation, while maintaining high code quality.  

Improve developer experience by reducing boilerplate, improving test coverage, simplifying local setup and documenting repeatable patterns.  

Move fluidly between infrastructure and product delivery when needed.  

Experience with Azure services, especially Blob Storage, Key Vault, managed PostgreSQL, managed Redis and containerised application hosting.  

Experience with enterprise authentication, especially Azure MSAL, OAuth/OIDC, token refresh, redirects and test-time auth bypasses.  

Experience with RAG, embeddings, vector search, document chunking, retrieval evaluation or LLM orchestration.  

Experience building legal tech, contract intelligence, document automation or professional services software.  

Familiarity with Radix UI, shadcn/ui, Tailwind CSS and design-token-first frontend systems.  

Experience with rich text or structured editing tools such as TipTap, Markdown editors or custom editor frameworks.  

Experience with Vite, code splitting, bundle monitoring, lazy loading and performance optimisation.  

Experience with Application Insights, OpenTelemetry or similar production telemetry systems.  

Familiarity with secure software delivery in ISO-compliant or enterprise client environments.