AI Engineer

Our client builds an enterprise LLM gateway. We are looking for a Senior Full-Stack Engineer to build production SaaS features across backend and frontend, focusing on payments/billing and gateway guardrails/telemetry. You will work with Python, FastAPI, React, TypeScript, Kubernetes, and Terraform.

• Payment system integration (primary focus): Design and build the billing layer end to end — integrate Stripe (or an equivalent provider) for subscription plans, metered/usage-based charging, invoicing, credits and prepaid balances, and payment lifecycle handling.
• LLM gateway guardrails (primary focus): Design and implement the policy layer that inspects traffic flowing through the gateway.
• Telemetry and observability (primary focus): Extend the request telemetry pipeline that powers customer-facing analytics — enriching per-request records with cost, token, cache, routing, and guardrail metadata, building efficient time-series aggregations.
• Gateway middleware: Build Python hooks inside the LLM proxy. Work includes prompt compaction, model routing based on request complexity, semantic caching, and response enrichment. Keep request handling correct and latency low.
• Backend API development: Build and evolve FastAPI services with async SQLAlchemy and PostgreSQL, including multi-tenant data isolation, RBAC, session-based authentication, encrypted secret storage, and Alembic migrations.
• Frontend development: Build customer-facing features in React and TypeScript — billing and plan management, guardrail configuration, telemetry and spend analytics views, admin/provisioning screens, and the LLM playground with streamed responses.
• Multi-provider model management: Extend provider integrations, model catalogues, budgets, and rate limits so tenants can bring their own models and providers safely.
• Own features end to end across the gateway middleware, backend API, and frontend — including schema design, API contracts, UI, tests, and rollout.
• Build and operate the subscription and usage-based billing system, including payment provider integration, webhook reliability, usage-to-invoice mapping, and entitlement enforcement.
• Design and implement guardrails that inspect and enforce policy on LLM prompts and completions, with per-tenant configuration and full auditability.
• Extend the telemetry pipeline and analytics aggregations that power customer-facing cost and usage reporting, and add tracing, metrics, and alerting across services.
• Write middleware that runs in the live request path, treating latency, failure modes, and graceful degradation as first-class design concerns.
• Design multi-tenant data models with correct isolation between organizations, workspaces, and keys.
• Write meaningful automated tests for the code you ship.
• Participate in architecture decisions, code reviews, and planning; document decisions for a distributed team.
• Handle sensitive data responsibly — secret encryption at rest, least-privilege access, and audit logging.

• 5+ years of professional full-stack experience. You have built and shipped production SaaS features across the backend and frontend.
• Strong Python skills and experience building production APIs with FastAPI (or Django REST / Flask, with a willingness to work in FastAPI), including async programming
• Strong React and TypeScript skills — comfortable with component-driven UI, SPA state management, routing, and integrating REST APIs including streamed responses
• Practical familiarity with LLM integrations, retrieval-augmented generation (RAG), AI agents, or AI tools such as Cursor, Claude Code, or Copilot. You do not need an AI research or specialist agent infrastructure background.
• Experience with Stripe or a similar payment provider. Relevant work includes subscriptions, webhooks, idempotency, proration, refunds, and usage-based billing in production.
• Solid PostgreSQL skills: schema design, migrations, indexing, and query optimization — including aggregations over large event/log tables
• Experience with multi-tenant architectures, authentication and authorization, and tenant data isolation
• You can use Docker and run services in Kubernetes. You can read a Helm chart and debug a failing pod.
• Experience with Redis or a comparable cache, and with designing for cache correctness and invalidation
• You work well in a startup with limited structure. You clarify unclear problems, choose practical solutions, and deliver them with little oversight.
• Clear written and spoken English for collaboration and documentation

• No micromanagement
• Freedom to engage in decision-making and implementation
• Ability to work in a team of professionals (the ratio of middle and above specialists 80/20)
• Participation in the development of high-quality products
• Direct communication with clients on a partnership level
• Health insurance
• A $1,000 flexible benefits budget per individual year
• 20 paid working days off and 10 days sick leave
• Opportunity to work remotely