jobapplier

Staff Full Stack Engineer (Internal Tools)

Lilt

Skills

Required

  • Slack
  • agreement metrics
  • Python
  • Go
  • SSO
  • integrations
  • applied-statistics / ML-adjacent
  • audio-quality scoring
  • debugging and optimizing native-library
  • numpy / scipy / onnxruntime-class
  • FastAPI
  • SQLAlchemy / Postgres
  • Java

Preferred

  • LLM-as-judge / LLM-based
  • QA/review pipelines
  • LLM provider gateway/routing services
  • OpenRouter
  • budget enforcement
  • implementing short-lived, rotatable service-to-service
  • GitHub
  • Docker
  • Terraform

Join our team as a Staff Full Stack Engineer, where you will play a crucial role in the development and maintenance of our internal tools. You will own significant surface area across architecture, data-pipeline design, and hands-on engineering, directly impacting the delivery of high-quality AI solutions. This high-impact, high-visibility role will require you to drive the long-term technical strategy for internal platforms and partner with various teams across the business. You will also have the opportunity to raise the engineering bar for our small, high-leverage team.

Responsibilities

  • Posséder une surface significative dans l'architecture, la conception des pipelines de données et l'ingénierie pratique pour maintenir l'infrastructure fiable.
  • Conduire la stratégie technique à long terme pour les plateformes internes tout en travaillant directement avec les équipes de livraison, d'exploitation et d'ingénierie.
  • Élever le niveau technique d'une petite équipe à fort impact en effectuant des revues de code, des documents de conception et du mentorat.
  • Experience building Slack (or comparable chat-platform) bot integrations that automate internal workflows — resource provisioning, approvals, budget/TTL enforcement — with real operational guardrails, not just CRUD features
  • Strong React/TypeScript frontend experience — component architecture, state management (Zustand, Redux, or similar), and a modern data-fetching layer (TanStack Query or comparable)
  • Solid grasp of CI/CD, containerized deployment (Docker, Helm, ArgoCD/GitOps or comparable), and infrastructure-as-code (Terraform or comparable)
  • Experience building ChatOps-style automation — Slack or GitHub PR-comment bot commands that trigger backend workflows or CI/CD runs

Requirements

  • Comfort reading and extending applied-statistics or ML-adjacent code (agreement metrics, audio-quality scoring, or comparable data-quality tooling)
  • Experience debugging and optimizing native-library (numpy/scipy/onnxruntime-class) memory growth in long-running Python worker processes via safe, boundary-aware process recycling — not just raising memory limits
  • Experience building and owning internal platforms/tools that increase leverage for a non-engineering team (research, operations, support, data/workforce management, or similar) — not solely external-customer-facing product work
  • Experience building and operating background job/worker systems (queue-driven or polling-based) with failure tolerance and idempotency in mind
  • Deep experience with a Python backend framework (FastAPI or comparable) plus async SQLAlchemy/Postgres, alongside production experience in at least one statically-typed backend language (Go, Java, or similar)
  • 5+ years of professional full-stack software engineering experience, with a track record of owning production systems end-to-end across more than one runtime/language
  • Experience integrating with third-party and platform APIs — including the GitHub API, OAuth/OIDC SSO, and at least one LLM API (Gemini, OpenAI, or similar) — handling auth, rate limits, and webhook-driven sync
  • Familiarity with OpenTelemetry or comparable observability instrumentation in Go services
  • Comfort owning both sides of a system with genuinely different runtimes without a large team to lean on
  • Experience designing abstractions over heterogeneous data sources with different consistency guarantees — e.g. a fully-replayable event history vs. an observe-only current-state API requiring synthesized diffing — behind one common interface
  • Notification and delivery systems experience — Slack bot integrations, transactional email, and idempotent delivery guarantees
  • Experience with inter-annotator agreement or statistical agreement metrics
  • Experience with audio/speech pipelines: ASR (Whisper or similar) or audio-quality metrics (DNSMOS, librosa)

Preferred

Experience with LLM-as-judge or LLM-based QA/review pipelines

  • Familiarity with LLM provider gateway/routing services (OpenRouter or comparable) — model aliasing, rate-limit and timeout handling, and budget enforcement
  • Experience building internal tools for managing a data-labeling, annotation, or crowdsourced-contributor workforce (vetting, QC, payments)
  • Experience implementing short-lived, rotatable service-to-service JWT auth (key-ID-based rotation, replay-protected tokens, fail-fast config validation) alongside a separate human-facing SSO flow in a paired service
  • Experience with data export/reporting tools (Excel generation, CSV pipelines, or BI-style dashboards)
  • Prior experience as the primary or sole engineer on a small, high-leverage internal platform

Pay

USD 190,000 - 230,000