Staff Fullstack Engineer - Internal Tools
Staff fullstack engineer on LILT's Internal Tools group, building and running the internal workforce-management, benchmarking, and QC platforms behind LILT's Applied AI benchmarking business for frontier AI labs. Day-to-day: own architecture, data pipelines, background workers, and ChatOps automation across a Python/FastAPI + Postgres backend, React/TypeScript frontend, and Go services.
- Compensation
- $177K–$221K / yr
- Location
- USA
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Fullstack
- Posted
Skills
Must have
- 5+ years professional full-stack software engineering experience 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
- 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 with failure tolerance and idempotency
- Experience integrating third-party and platform APIs, including GitHub API, OAuth/OIDC SSO, and at least one LLM API (Gemini, OpenAI, or similar), handling auth, rate limits, and webhooks
- Experience building Slack (or comparable) bot integrations automating internal workflows with real operational guardrails
- Comfort reading and extending applied-statistics or ML-adjacent code (agreement metrics, audio-quality scoring, or comparable)
- Solid grasp of CI/CD, containerized deployment (Docker, Helm, ArgoCD/GitOps or comparable), and infrastructure-as-code (Terraform or comparable)
- Experience debugging native-library memory growth in long-running Python workers via boundary-aware process recycling
- Experience building and owning internal platforms/tools that increase leverage for a non-engineering team
Nice to have
- Experience with audio/speech pipelines: ASR (Whisper or similar) or audio-quality metrics (DNSMOS, librosa)
- Experience building internal tools for managing data-labeling, annotation, or crowdsourced-contributor workforces (vetting, QC, payments)
- Experience with inter-annotator agreement or statistical agreement metrics
- Notification and delivery systems experience: Slack bot integrations, transactional email, idempotent delivery guarantees
- Experience designing abstractions over heterogeneous data sources with different consistency guarantees behind one common interface
- Experience building ChatOps-style automation (Slack or GitHub PR-comment bot commands triggering backend workflows or CI/CD runs)
- Experience implementing short-lived, rotatable service-to-service JWT auth alongside a separate human-facing SSO flow
- 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
- 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, budget enforcement
- Experience with data export/reporting tools (Excel generation, CSV pipelines, or BI-style dashboards)
Full description
About LILTAI 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.
At LILT, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues—Work together, win together; Find a way or make one; Dance in the customer's shoes; Quicker than they expect; Quality is Job 1—guide everything we do. We are trusted by Intel Corporation, Canva, the United States Department of Defense, the United States Air Force, ASICS, and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we’re building a category-defining company in a $50B+ global translation market being redefined by AI.
As part of LILT’s Internal Tools group, you will build and run the tools that LILT's own delivery, contributor-ops, and engineering teams rely on to operate LILT's Applied AI (AAI) benchmarking business — which builds and delivers multilingual benchmarks and evaluation data to frontier AI labs using LILT's global network of subject-matter experts. As the AAI business grows, expect the scope of these platforms to grow in parallel. This platform sits directly on the critical path of paid customer deliverables with real SLAs, maintained by a small, high-leverage engineering team that produces reliable, production-ready tooling. You will own significant surface area across both end-to-end: architecture, data-pipeline design, and the hands-on engineering that keeps this infrastructure reliable. This is a high-impact, high-visibility role: the reliability and craft you bring directly enables on-time, high-quality delivery for some of the most prominent AI labs in the world.
In this role, you will drive the long-term technical strategy for internal platforms while working directly with the delivery, ops, and engineering teams across the business who depend on them daily. This team ships cross-service automation in careful stages — advisory first, then assistive, only later decision-relevant, always with a human fallback — and you'll be expected to hold that same bar as you extend these systems. You will partner with a small existing team to raise the engineering bar across two very different runtimes, set technical direction, and make the calls that determine how this infrastructure scales as the business grows.
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