Backend Engineer

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.

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.

What You'll Do

• Build and maintain backend services for the real-time translation pipeline: audio ingestion, diarization hookups, streaming ASR/MT orchestration, and result fan-out to every configured meeting language

• Implement the event-driven routing logic that flags low-confidence segments and routes them to the correct on-call interpreter by language

• Build APIs and services backing the bot/agent participant and meeting side panel that deliver translation into the host meeting platform, with guidance from senior engineers

• Contribute to the interpreter correction and broadcast system — ensuring corrections are isolated to the correct language and broadcast to all participants in real time

• Write and maintain automated tests (unit, integration, e2e) and contribute to CI/CD pipelines (GitHub Actions) for new backend services

• Instrument services for observability — logging, metrics, tracing — to support debugging of latency-sensitive, multi-party sessions

• Partner with frontend/fullstack engineers on the Create team to define clean API contracts between backend services and the live meeting UI and interpreter workbench

• Participate in on-call rotation and help triage production issues as the product moves toward GA

• Help generate post-meeting assets: diarized transcripts, exportable formats (TXT/WebVTT/JSON), and per-line verification metadata

What We're Looking For

Required

• 2–5 years of professional backend software engineering experience, ideally including production systems that handle real-time or streaming data

• Experience building REST API endpoints as well as streaming services with WebSockets, gRPC, message queues, or comparable low-latency/event-driven patterns

• Solid experience with Node.js/TypeScript, Java, Python, or a comparable backend language/ecosystem, and the ability to work across more than one when needed

• Experience building and consuming REST/GraphQL APIs, including authentication patterns (OAuth, API keys/tokens, service accounts)

• Comfort with relational/NoSQL data modeling for session state, transcripts, and configuration data

• Solid grasp of testing and delivery practices: CI/CD and automated integration/e2e tests

• Ability to take a well-scoped ticket or spec and ship it with minimal oversight, while communicating blockers and timeline risk early

• US citizenship and residence in the United States

Strong Plus

• Experience with speech/audio pipelines: diarization, streaming ASR, or audio stream handling

• Experience integrating with third-party platform APIs, SDKs, or webhooks (Slack, Zoom, or similar collaboration platforms)

• Familiarity with localization/TMS workflows: XLIFF, Translation Memory, MT vs. human translation pipelines

• Experience with event-driven/pub-sub architectures (Kafka, Pub/Sub, or similar)

• Enough frontend/React exposure to reason about API contracts with a real-time, stateful UI

Bonus

• Hands-on Microsoft Teams app or bot development specifically (Teams Toolkit, Bot Framework, Azure Communication Services, Microsoft Graph)

• Experience working on 0-to-1 products within a larger, established company

• Interest or coursework in NLP/ML systems

• Experience with observability tooling (e.g., Datadog) in production, latency-sensitive systems