GTM Engineer
Role Summary
Join Lilt Corporate as a GTM Engineer in London, driving AI-powered go-to-market strategies in a leading translation company.
About the Organisation
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.
Key Responsibilities
This high-impact, hands-on role is responsible for owning LILT's agentic GTM systems: proposing, designing, building, and maintaining the AI-driven tools and automations that power our go-to-market engine, including our Clay-based enrichment and outbound workflows. You'll also play a critical role in optimizing our go-to-market technology stack, streamlining our lead-to-opportunity process, and helping to maintain day-to-day department operations.
You'll work closely with GTM leadership across Sales Development, Sales, Marketing, and Operations and Systems functions to drive process optimization and overall efficiency. You'll recommend, build, and run cross-functional projects and process improvements that directly impact our operational efficiency and top-line growth of all revenue lines. You'll contribute to the strategy and execution of full-funnel programs that drive predictable, scalable pipeline.
- Agentic business systems integration. Propose, design, build, and maintain agentic AI tools and automations that connect and orchestrate our GTM stack end-to-end, reducing manual work and increasing the speed and reliability of our lead-to-revenue motion.
- Own Clay and the automation stack. Serve as our resident expert on Clay (and similar enrichment/orchestration tools), building and maintaining tables, waterfalls, and workflows that keep our data accurate and our outbound motion running.
- Salesforce lead-to-opportunity. Partner closely with RevOps to own the workflow from a new lead entering the system, through the various lead stages, and converting to an opportunity, including routing, assignment, and the rules that decide who works what.
- Full-funnel ownership. Design and optimize the entire lead funnel, from top-of-funnel acquisition through MQL to SQL handoff, driving higher conversion and increased velocity.
- Lead and contact data integrity. Work with internal tools and external vendors to maintain a high quality database of contacts across our target industries and personas.
- Partner with Sales. Align tightly with revenue leadership to define pipeline goals, campaign targeting, SLAs, and lead management workflows. Sit close enough to the reps to know which parts of the process actually hurt.
- Fuel growth. Partner closely with the demand gen team to drive multi-channel campaigns across email marketing, webinars, paid media, SEO, events, outbound motions, and ABM to meet ambitious growth targets.
- Use data to scale. Build a data-driven culture. Forecast, measure, and communicate program results, continuously optimizing for ROI and CAC efficiency.
- Collaborate cross-functionally. Work across demand gen, product marketing, ADRs, and sales ops to build cohesive, conversion-optimized systems and campaigns.
- Department operations. Help with department-level planning for things like managing campaign budget, team meetings and activities, and annual planning.
- Documentation and knowledge continuity. Maintain living documentation (Notion) for every agent and workflow you own, to a standard where a new team member or another AI agent could pick up ownership without a live handover call. This is a stated expectation of the role, not an afterthought.
Minimum Requirements
- 3-5 years in B2B SaaS or AI/ML go-to-market engineering, RevOps, or marketing operations, with a track record of building automations that actually ship.
- Hands-on Clay expertise. You've built waterfall enrichment, scoring, and routing in Clay (or a comparable tool), and you can take a new use case from idea to live quickly.
- Agentic AI and automation fluency. Comfortable proposing, designing, and building agentic workflows and integrations using APIs, webhooks, and orchestration tools, to connect systems and eliminate manual work.
- Working proficiency in Python/other languages for building and maintaining AI agent pipelines. Comfortable working inside an existing codebase, not just writing standalone scripts.
- Comfortable reasoning about tradeoffs under cost and token constraints. You can explain not just what you built, but why you didn't build the more expensive or more complex version.
- Strong Salesforce fundamentals. You can build reports, understand the object model and the automation layer, and use what you find to change how the funnel actually performs.
- A point of view on where AI in GTM is heading. We'll ask. We're less interested in whether we agree than in whether you've thought about it seriously.
- Obsessed with the metrics that matter: MQLs, pipeline, bookings, funnel conversion, velocity, CAC, and ROI.
- Familiarity with marketing automation platforms (HubSpot or similar) a plus.
- Ability to build relationships and work cross-functionally.
- Smart, curious, and hard-working.
- Natural collaborator and communicator, comfortable presenting to executives, boards, and cross-functional stakeholders.
Eligibility Criteria
Eligibility details are not clearly stated in the job description.
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