Senior AEM 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; 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 AEM Connector enables enterprise customers to push and pull AEM content — Sites pages, Content Fragments, Assets, and Tags — directly through Lilt's translation platform, supporting both Instant Translate and Verified Translation workflows. Every customer who runs AEM has a unique content topology, and making the connector work reliably across that diversity is a real engineering challenge. You will own the connector end-to-end: architecture, product roadmap, and the hands‑on technical advisory work that ensures enterprise deployments succeed in the field. This is a high‑impact, high‑visibility role on a product with a growing customer base that includes some of the world's largest global brands. As the senior engineer on the AEM Connector, you will drive the long‑term technical strategy for the connector while working directly with enterprise customers — configuring implementations, diagnosing production issues, and establishing the best practices that define how Lilt and AEM work together. You will partner with Solutions and Account teams, train internal staff, and build the validation and guard logic that prevents customer‑specific content structure quirks from becoming production incidents. You will ship new capabilities, validate, and define the canonical site structures the connector explicitly supports. What You'll Do Own the connector architecture and long‑term product roadmap for the Lilt AEM Connector Define and maintain the canonical AEM site structures the connector explicitly supports — and advise customers on how their specific topology maps to those structures (or where it diverges) Guide customers through AEM Translation Integration Framework setup: language masters, language copies, MSM/Live Copy topology, Experience Fragment hierarchies, and cloud configurations relative to Lilt's connector Work directly with enterprise customers to capture feature requirements, validate configurations, and establish long‑term best practices Define and document canonical patterns for translation project creation, Content Fragment localization, DAM asset translation, and auto‑archiving workflows Partner with Solutions and Account teams for pre‑sales technical evaluation, onboarding, and escalation triage Train and enable internal teams on connector capabilities, OSGi configuration options, and troubleshooting patterns Deliver new connector capabilities through the full cycle: CI (GitHub Actions), E2E Cypress tests, package deployment via Cloud Manager and RDE What We're Looking For 5+ years of professional AEM development on AEM Cloud Service (AEMaaCS), with a track record of owning a production AEM implementation end‑to‑end — architecture, implementation, deployment, and field reliability Deep knowledge of AEM content architecture: JCR/Sling resource model, OSGi service components, AEM Sites, DAM, and Content Fragments Java/OSGi bundle authoring: services, schedulers, Sling jobs, event listeners, servlets, and Sling Models Deep understanding of AEM Translation Integration Framework: language master setup, language copies, Translation Projects, Translation Jobs, and MSM/Live Copy inheritance hierarchies Fluency in AEM content topology nuances — including where standard Adobe guidance does not apply (e.g., Experience Fragments outside language master hierarchies, non‑page trunk nodes, customer‑specific site structures that would never appear in Adobe's sample sites) Ability to debug JCR node type conflicts and content tree issues across diverse customer environments Customer‑facing technical experience: configuring AEM environments, leading implementation workshops, writing best‑practices documentation, and guiding enterprise rollouts Comfort reasoning about complex multilingual content topologies — multi‑region, multi‑language‑copy sites, shared Live Copy inheritance Strong Plus Prior AEM connector or TMS connector development (Sling connector framework, Translation API integration, XLIFF handling) Content Fragments, Experience Fragments, and Headless AEM (GraphQL / Content Services) OSGi configuration management — including config file authoring, Felix console operations, and Repoinit scripting AEM Cloud Manager, RDE (Rapid Development Environments), and package deployment lifecycle Experience navigating plugin interplay in complex AEM environments where multiple third‑party extensions are installed Adobe I/O Events or AEM Eventing for reactive/webhook‑based integration patterns AEM security model: service users, CUGs, replication agents, and permission‑aware content access Bonus Prior experience building or maintaining a packaged AEM extension or AEM archetype‑based product Familiarity with AEM Launches (content fork/stage/merge workflows) and how they interact with translation pipelines Familiarity with localization/TMS workflows: XLIFF, Translation Memory, MT vs. human translation pipelines AEM certifications (Developer or Architect) Experience with Cypress‑based E2E testing in an AEM environment 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 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 View email address on click.appcast.io. 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. #J-18808-Ljbffr