SectorResidential/ Multifamily Real Estate Innovation
Salary50,000 - 75,000 / Year
Our client is a high-growth technology business looking for a GTM Engineer to build and optimise the systems that underpin its commercial operations.
About the Role Our client is a high-growth technology business looking for a Go-to-Market (GTM) Engineer to build and optimise the systems that underpin its commercial operations. This is a highly technical, hands-on engineering position focused initially on Sales and Marketing, with the opportunity to extend automation and AI-driven systems across the wider organisation. Rather than operating in a traditional pre-sales capacity, the successful candidate will focus on identifying manual, inefficient workflows and engineering scalable systems to replace them. The initial priority will be revenue operations, building the infrastructure behind lead generation, enrichment, prioritisation and pipeline management so commercial teams have accurate, actionable information at their fingertips. Key Responsibilities
Build and maintain high-quality commercial datasets that provide a comprehensive view of the organisation’s target market, customers and prospects.
Design and automate lead sourcing, enrichment, matching, deduplication, segmentation and scoring processes.
Build systems that enable Sales teams to work from accurate, prioritised and actionable prospect lists.
Automate repetitive sales administration, including pre-call research, CRM management, follow-ups, call notes, proposals and pipeline reporting.
Develop the underlying systems and infrastructure supporting Marketing, including audience data, workflow automation and channel-level performance tracking.
Own and optimise inbound lead workflows, covering capture, enrichment, qualification, routing and initial response.
Build reliable commercial reporting that enables leadership to make informed decisions based on accurate data.
Treat commercial data as a product, ensuring it remains accurate, current, deduplicated, traceable and appropriately managed in line with relevant data protection requirements.
Identify high-cost or time-consuming manual processes across areas such as onboarding, Customer Success, Finance, Operations and Recruitment, and develop automation to improve them.
Build internal tools and workflows that are practical, scalable and widely adopted by the business.
Implement appropriate monitoring, error handling, documentation and human checkpoints to ensure automated systems remain reliable.
Work directly with non-technical stakeholders to understand existing processes and rapidly translate business problems into effective technical solutions.
Measure the commercial impact of systems and automation, continuously improving them based on adoption, efficiency and business outcomes.
Requirements
2–5 years of relevant professional experience, potentially gained within software engineering, technical product, data, consulting, automation, start-ups or another highly technical environment.
Strong software development capabilities, with experience writing production-quality code using Python, TypeScript or similar technologies.
Strong working knowledge of APIs, databases, data integrations and automation.
Practical experience using LLMs and AI technologies to build solutions beyond basic prompting, such as agents, tool-use systems, retrieval workflows, evaluations or autonomous processes.
Evidence of building automation or internal systems that have delivered measurable value to a business, ideally within or adjacent to Sales and Marketing.
Strong understanding of commercial processes and metrics, including sales funnels, pipeline performance and conversion.
Experience working with data enrichment, matching, deduplication and data-quality processes.
A strong technical or quantitative academic background, such as Computer Science, Engineering, Mathematics, Physics or a related discipline.
Commercially minded, with the ability to distinguish between technically interesting solutions and those that create meaningful business value.
High level of ownership and a strong bias towards execution, with the ability to move quickly from identifying a problem to delivering a usable solution.
Excellent ability to translate complex business challenges into actionable technical solutions and insights.
Comfortable collaborating directly with both technical and non-technical stakeholders.
Experience with modern GTM technology, including CRM automation, data enrichment, orchestration and analytics platforms, would be advantageous.
Experience with AI development tools, agent frameworks, APIs and tool-integration protocols would be beneficial.
Previous experience within B2B SaaS, particularly businesses selling to SMEs or operating within vertical markets, would be advantageous.
Experience in roles such as Technical Product Manager, Forward-Deployed Engineer, Solutions Engineer, Growth Engineer, Revenue Operations Engineer or Technical Founder would also be highly relevant.
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"We had a highly specific set of criteria for our search, and the LMRE team delivered exceptionally well. Marisolea led the process and was able to identify a candidate who not only met all of our requirements but also demonstrated genuine enthusiasm and passion for our company’s vision.
The candidate even remarked that they were surprised Marisolea had discovered their profile, as it wasn’t immediately obvious they were open to new opportunities, a true testament to her ability to uncover hidden talent.
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"Hey, I'm Chief Product Officer at Canvas. We engaged with LMRE through our CEO connection. And I'm happy we did! We were looking for a Product Manager for our Operations team. We needed not just a great PM but a subject matter expert in BIM (Building Information Modeling) space. At first, we thought that we might be looking for a unicorn, so we even increased the search geography from Europe to Europe+US. Luckily, LMRE were able to provide us with a flow of high-quality candidates. Lacey and the team have done great screening so most of the candidates have been advanced to multiple interview steps. And in ~1.5 months, we've hired an amazing candidate who checked all the boxes. I would highly recommend working with LMRE for at least very specialized roles in ConTech."
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Shai Kivity, Chief of Staff at 4M AnalyticsClient
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