Solutions AI Architect (Pre-Sales) (Expression of Interest)

LILT AI
London
2 months ago
Applications closed

Related Jobs

View all jobs

Data & AI Solution Architect, Azure, Remote

AI) Machine Learning Research Engineer

Director of Generative AI | Remote

Data Science Manager – Gen/AI & ML Projects - Bristol

Machine Learning and AI Engineering Lead

Machine Learning Engineer, Amazon Studios AI Lab

LILT in the News

About Us

LILT is the leading AI solution for enterprise translation. Our stack made up of our Contextual AI Engine, Connector APIs, and Human Adaptive Feedback enables global organizations to adopt a true AI translation strategy, focusing on business outcomes instead of outputs. With LILT, innovative, category-defining organizations like Intel, ASICS, WalkMe, and Canva are using AI technology to deliver multilingual, digital customer experiences at scale.

While our core AI technology might share similarities with ChatGPT and Google Translate, it's what we do with it that makes LILT truly revolutionary. Our patented Contextual AI Engine goes beyond basic translations, understanding the nuance of our customer's content and target audience to deliver hyper-accurate, business-focused results. Our connector-first approach seamlessly integrates with our customer's existing workflows, and our human-adapted feedback loop ensures continuous improvement, making LILT a constantly evolving AI partner for your global ambitions.

The Solutions Team at LILT

LILT’s Solutions team focuses on our industry AI leading technology and its application to multilingual content requirements for large enterprises as well as government agencies. Our team engages with customers from the pre-sales/prospect stages through post-sale/customer onboarding stages and is made up of experts in various functional and technical areas of LILT’s overall offering. While we work in various locations, we are highly collaborative within the team and have tight interactions with our colleagues in the LILT Sales, Product, Engineering and Services teams. Additionally, we operate as critical members of account-based teams that ensure LILT’s technology is utilized to deliver maximum value to our customers.

Where You’ll Work

This position can be based out of our London, UK or Berlin, Germany offices and will be expected to work in the office in a hybrid capacity. Get the best of both worlds at LILT! Dive into dynamic in-office energy 2 days a week, sparking creativity and forging bonds with your awesome team. Then, seamlessly shift gears and crush your to-do list from the comfort of your home base for the rest of the week. It's the perfect harmony of productivity and personal freedom.

Authorization to work in the UK or Germany is a precondition of employment.

What You’ll Do

We're looking for an experienced Solutions Architect who loves solving hard problems, managing complex projects, and interacting with a variety of stakeholders. This position is for someone who has strong technical aptitude, extensive customer-facing experience, and the ability to manage multiple complex projects at once.

You will work hand-in-hand with Sales, Product, Engineering, Services, and Marketing teams to bring our platform to clients and prospects. You will be responsible for providing the technical expertise in sales pursuits to drive LILT customer acquisition and success. You will have a broad range of skills and experience ranging from global content management lifecycle, a working knowledge of NLP/MT, TM, glossary, and content pipelines and integrations. You will have the insight to make the connection between a customer’s specific business problems and LILT's solution, the customer-facing skills to communicate that connection and vision to a wide variety of technical and executive audiences, and the technical skills to be able to not only build demos and execute proof-of-concepts but also to provide consultative assistance on architecture and implementation.

Key Responsibilities:

  • Serve as the technical co-pilot to LILT Account Executives and Account Managers, managing the customer’s technical experience from scoping (pre-sales) to deployment (post-sales / success).

  • Build and present references architectures, how-tos, and demo applications for customers.

  • Be a subject-matter expert in translation and localization process optimization and best practices.

  • Understand and align customer’s technology stack to optimize localization processes.

  • Work closely with Engineering, Product, and Account Management teams to ensure smooth prospect-to-customer transitions and long-term customer success.

  • Play an active role in the development and maintenance of client-integrations.

  • Develop and iterate on internal processes to ensure consistency across our solutions engagements.

  • Track existing technology solutions and follow the latest trends and developments relevant to multilingual content management and translation; specifically the application of AI.

Skills and Experience:

  • REQUIRED:

    • Fluent in both English and German.

    • At least 4+ years of experience in a technical pre/post-sales role at a language services, language technology, or content management company.

  • Experience working with a complex services-oriented solution.

  • Proven ability to communicate, present, and influence credibly and effectively at all levels of the organization, including executive and C-level.

  • Subject matter expertise in localization solutions, technologies, and processes.

  • Experience in localization engineering highly desirable.

  • TMS and CAT Tool familiarity highly desirable.

  • Familiarity with integrating CMS systems to translation workflows highly desirable.

  • Familiarity with Large Language Models, including fine tuning, highly desirable.

  • A passion for technical and solution-based problem solving.

  • Analytical approach to intelligence gathering and project planning.

  • Outstanding verbal and written communication skills; ability to interact easily with end users and C-level executives.

  • Keen attention to detail and adherence to deadlines.

  • Strong desire to learn in a rapidly growing and dynamic pre-IPO growth environment.

  • Self-motivated and inspired by a results-driven environment.

  • Confidence communicating technical ideas to various audiences, primarily through presentations, whiteboarding, and platform demonstrations.

  • Comfort with a bit of chaos, startup experience is an advantage.

  • Ability to work independently and self-sufficiently while being part of a team and pursuing team goals.

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. They were amazed to learn that Google Translate wasn’t used for enterprise products and services inside the company and left to start a new company to address this need – LILT.

At its core, LILT has always been a machine learning company since its incorporation on March 6, 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, believing that this foundation was imperative to the future of enterprise translation.

BenefitsUnited Kingdom

  • Compensation: At market salary, meaningful equity, pension scheme contribution, and time off plus company holidays.

  • Health care: Employees receive coverage of medical, dental, and vision insurance. LILT pays for basic life assurance.

  • Monthly lifestyle benefit stipend via the Fringe platform to allow employees to customize benefits to their lifestyle.

Germany

  • Compensation: At market salary, meaningful equity, and time off plus company holidays.

  • Monthly lifestyle benefit stipend via the Fringe platform to allow employees to customize benefits to their lifestyle.

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 athttps://lilt.com/legal/privacy. 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

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.