Staff Fullstack Engineer - Internal Tools

About LILT

AI is changing how the world communicates — and LILT is leading that transformation.

We're on a mission to make the world's information accessible to everyone, regardless of the language they speak. We use cutting-edge AI, machine translation, and human-in-the-loop expertise to translate content faster, more accurately, and more cost-effectively without compromising on brand, voice, or quality.

What You'll Do

• Partner with the benchmarking business's researchers and TPMs to translate new benchmark and data-quality requirements into scoped technical designs

• Own the internal workforce-management tools on our internal platform for AI delivery for hundreds of external contributors: vetting flows, candidate assessment, QC, payment/delivery tracking, and roster/reporting exports

• Own architecture and long-term technical direction across multiple services and the platform

• Extend IAA and audio-QA pipelines: annotator outlier detection, ASR sidecar enhancements, LLM-based QC, and DNSMOS/librosa audio-quality scoring

• Design and ship new modules on the platform that plug new benchmark and vetting workflows into the existing multi-stage review lifecycle

• Own and extend the platform's API key provisioning and budget-governance system

• Build self-serve ChatOps-style automation for the internal engineering org and contributor base to enable accelerated annotator workflows and query resolution

• Harden background worker and job-processing infrastructure

• Set and enforce testing, CI/CD, and deployment practices across both codebases — from unit/integration testing through infrastructure-as-code and release automation

• Raise the technical bar for a small, high-leverage team through code review, design docs, and mentoring as the surface area grows

What We're Looking For

Required

• 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

• 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)

• Strong React/TypeScript frontend experience — component architecture, state management (Zustand, Redux, or similar), and a modern data-fetching layer (TanStack Query or comparable)

• Experience building and operating background job/worker systems (queue-driven or polling-based) with failure tolerance and idempotency in mind

• 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

• 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

• Comfort reading and extending applied-statistics or ML-adjacent code (agreement metrics, audio-quality scoring, or comparable data-quality tooling)

• Solid grasp of CI/CD, containerized deployment (Docker, Helm, ArgoCD/GitOps or comparable), and infrastructure-as-code (Terraform or comparable)

• 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

Strong Plus

• Experience with audio/speech pipelines: ASR (Whisper or similar) or audio-quality metrics (DNSMOS, librosa)

• Experience building internal tools for managing a data-labeling, annotation, or crowdsourced-contributor workforce (vetting, QC, payments)

• Experience with inter-annotator agreement or statistical agreement metrics

• Notification and delivery systems experience — Slack bot integrations, transactional email, and idempotent delivery guarantees

• 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

• Experience building ChatOps-style automation — Slack or GitHub PR-comment bot commands that trigger backend workflows or CI/CD runs

• 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

• Comfort owning both sides of a system with genuinely different runtimes without a large team to lean on

• Prior experience as the primary or sole engineer on a small, high-leverage internal platform

Bonus

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

• Familiarity with OpenTelemetry or comparable observability instrumentation in Go services

• Familiarity with LLM provider gateway/routing services (OpenRouter or comparable) — model aliasing, rate-limit and timeout handling, and budget enforcement

• Experience with data export/reporting tools (Excel generation, CSV pipelines, or BI-style dashboards)