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.

Lilt's Converse product delivers real-time, multi-party translation for high-stakes conversations — from offline, device-based deployments in the field to live meetings on enterprise collaboration platforms. We're expanding Converse to support any number of participants, speaking any combination of languages, joining from a growing set of form factors — with live translation delivered N-way, directly on the meeting stage, and cleared interpreters reviewing only the segments that need a human eye. Every deployment has a different topology — device count, platform, network conditions, and language mix — and making a single translation architecture work reliably across that diversity is a real engineering challenge. You will help own this expansion end-to-end: architecture, product roadmap, and the hands-on engineering that gets a brand-new real-time product surface to GA. This is a high-impact, ground-floor role on a new product line within a company whose existing products serve some of the world's largest global brands.

As the senior engineer on the Create team driving this Converse expansion, you will drive technical strategy for both the backend translation service and the customer-facing surfaces built on top of it, while working directly with Product, Design, and early design partners — architecting the low-latency streaming pipeline, building the live meeting experience and interpreter workbench, and turning ambiguous 0-to-1 requirements into a scoped plan you commit to and ship. You will partner with the engineers already building Converse's device/mobile experience to extend a shared translation-service architecture into new platforms and form factors, help define engineering standards as the Create team grows, and make the calls that determine whether this expansion scales cleanly from a prototype into a production product used in live, multilingual meetings.

Location & eligibility: This position requires US citizenship and residence in the United States. Preferred locations are Washington, D.C.; Boston, MA; and Indianapolis, IN.

What You'll Do

• Own architecture and technical roadmap for this Converse expansion, spanning the central real-time translation service and the customer-facing surfaces built on it (live meeting UI, interpreter workbench)

• Architect and build the low-latency, N-way translation pipeline: per-participant audio ingestion, diarization, streaming ASR, MT orchestration, and result fan-out to every language in the meeting

• Build the live meeting experience — bot/agent participant, meeting side panel, and on-stage caption surfaces — integrating with the host meeting platform's SDK, extension framework, and APIs

• Build the interpreter workbench: a real-time, streaming adaptation of Lilt's CAT tool with a live segment queue, low-confidence flagging, TM/TB matches, AI-Review/AI-QA signals, and submit-to-broadcast corrections

• Design the event-driven correction and broadcast system — routing flagged segments to the correct on-call interpreter by language, pausing the affected translation, and isolating each correction to a single language

• Partner with Product and Design to turn PRD requirements (JTBD, feature specs) into technical designs, and commit to and hit delivery dates on a brand-new product surface

• Collaborate with the engineers already building Converse's device/mobile experience to extend a shared translation-service architecture (per-participant declared spoken/received languages) into new multi-device and platform form factors

• Establish testing, CI/CD, and release practices (GitHub Actions, automated e2e tests) for the new product line

• Help recruit, mentor, and set engineering standards as headcount scales on this initiative

What We're Looking For

Required

• 5+ years of professional full-stack software engineering experience, with a track record of owning complex, real-time or streaming systems end-to-end — architecture, implementation, deployment, and production reliability

• Strong backend experience spanning REST API endpoints and real-time/streaming systems: WebSockets, gRPC, or comparable low-latency transport; event-driven architectures; message routing and state management across many concurrent sessions

• Strong frontend experience building complex, stateful, real-time UIs in React/TypeScript — live-updating multi-pane interfaces, collaborative editors, or comparable dashboards

• Experience integrating with third-party platform SDKs or extension frameworks (Slack, Zoom, or similar meeting/collaboration platforms) — bots, side panels, webhooks, and platform APIs

• Comfort working with or directly adjacent to ASR/MT/NLP pipelines, or other latency-sensitive ML-in-the-loop systems

• Demonstrated ability to scope ambiguous, 0-to-1 product requirements into a technical plan and commit to and hit delivery dates

• Experience building validation and guard logic that gracefully handles edge cases across diverse customer configurations — languages, device counts, network conditions

• US citizenship and residence in the United States

Strong Plus

• Experience with speech/audio pipelines: diarization, streaming speech recognition, or audio stream multiplexing

• Prior experience building CAT tools, translation memory/termbase systems, or other linguist-facing review interfaces

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

• Experience with cross-platform, embedded, or mobile-adjacent architectures, and adapting shared services across device and web form factors

• Experience shipping in regulated or high-security customer environments

Bonus

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

• Experience mentoring engineers and setting technical standards for a new product line

• Familiarity with post-meeting asset generation: transcript export formats (TXT/WebVTT/JSON), recording citations, and summarization

Our Story

Our founders, Spence and John met at Google working on Google Translate. As researchers at Stanford and Berkeley, they both worked on language technology to make information accessible to everyone. While together at Google, they were amazed to learn that Google Translate wasn’t used for enterprise products and services inside the company.The quality just wasn’t there. So they set out to build something better. LILT was born.

LILT has been a machine learning company since its founding in 2015. At the time, machine translation didn’t meet the quality standard for enterprise translations, so LILT assembled a cutting-edge research team tasked with closing that gap. While meeting customer demand for translation services, LILT has prioritized investments in Large Language Models, human-in-the-loop systems, and now agentic AI.

With AI innovation accelerating and enterprise demand growing, the next phase of LILT’s journey is just beginning.

Our Tech

What sets our platform apart:

• Brand-aware AI that learns your voice, tone, and terminology to ensure every translation is accurate and consistent

• Agentic AI workflows that automate the entire translation process from content ingestion to quality review to publishing

• 100+ native integrations with systems like Adobe Experience Manager, Webflow, Salesforce, GitHub, and Google Drive to simplify content translation

• Human-in-the-loop reviews via our global network of professional linguists, for high-impact content that requires expert review

LILT in the News

• Featured in The Software Report’s Top 100 Software Companies!

• LILT makes it onto the Inc. 5000 List.

• LILT’s continues to be an intellectual powerhouse, holding numerous patents that help power the most efficient and sophisticated AI and language models in the industry.

• Check out all our news on our website.

Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT's Privacy Policy at https://lilt.com/legal/privacy.

At LILT, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at recruiting@lilt.com.

LILT is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual’s race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable local, state or federal laws. We are committed to the principles of fair employment and the elimination of all discriminatory practices.