Jobs at Intercom

Lead the architecture and technical strategy for Fin’s web platform and marketing growth surfaces. Drive scalability, performance, observability, reliability, developer productivity, MarTech, experimentation, analytics, and attribution systems. Partner with marketing, design, data science, analytics, infrastructure, and engineering teams; mentor engineers; communicate technical trade-offs; and contribute hands-on to software development.

Own end-to-end product marketing for Operator, Fin’s AI agent for customer operations. Develop category-defining narratives, positioning, ICP and messaging; lead launches and go-to-market initiatives; create sales enablement, competitive positioning, web content, demos and other PMM assets. Partner with product, marketing, sales and leadership, conduct customer research, translate technical capabilities into clear value, and maintain messaging systems supporting Fin’s AI-first approach.

Lead product marketing for Fin’s Intercom helpdesk and AI-first customer support products. Own ICP definition, positioning, messaging, customer insights, launches, go-to-market strategy, sales enablement, and marketing assets. Partner cross-functionally with Product, Engineering, Sales, Customer Success, and Lifecycle teams to communicate product value, support retention and expansion, and establish Fin as the leader in AI-enabled helpdesk solutions.

Own the Messenger product channel for Fin, defining customer problems, roadmap, product vision, and release priorities. Collaborate with engineering, design, research, and cross-functional teams to build and launch AI-powered messaging experiences. Use customer research, data, and AI tools to guide decisions, measure outcomes, maintain product quality, and execute go-to-market strategies. Lead through influence, strong communication, ownership, and alignment with company values.

Own the vision, strategy, roadmap, and impact of a major AI platform or agent product area. Partner with ML scientists, engineers, researchers, designers, and cross-functional teams to turn advanced AI capabilities into valuable customer experiences. Lead experimentation, product launches, success measurement, performance evaluation, and iteration while ensuring safety, reliability, adoption, and business impact. Communicate decisions clearly, align stakeholders, and drive progress in an ambiguous, fast-moving environment.

Leads and scales EMEA Solutions Engineering, defining go-to-market strategy, coaching teams, supporting complex enterprise sales cycles, and delivering tailored AI platform solutions. Responsibilities include technical discovery, architecture, demonstrations, proofs of concept, business value assessments, executive customer engagement, reusable solution frameworks, verticalized assets, forecasting, and influencing product strategy. The role is a player-coach position requiring close collaboration with Sales, Product, Marketing, Engineering, Services, and Success.

Manage strategic, high-value enterprise customers throughout their Intercom and Fin journey. Build executive relationships, create success plans, lead QBRs and strategic planning, drive AI product adoption and expansion, mitigate churn, identify growth opportunities, and provide customer insights internally. Serve as a trusted advisor and thought leader across complex global customer service organizations.

Lead end-to-end deployments of Intercom and Fin for large customers, manage project scope and timelines, perform hands-on configuration and integrations, coordinate technical readiness and data migrations, track adoption and outcomes, and partner cross-functionally to deliver measurable AI-driven customer support results.

As a Senior Machine Learning Scientist, you will identify ML opportunities, design algorithms, conduct analyses, and collaborate with product teams to build effective ML solutions for customer service enhancement.

As a Senior Forward Deployed Engineer, you will work closely with customers to implement AI solutions, drive adoption, and enhance their support operations while collaborating with sales and product teams.

As a Staff Forward Deployed Engineer, you will lead customer engagement, help integrate AI solutions, and mentor engineers while collaborating cross-functionally to enhance customer service capabilities.

Design, build, and maintain end-to-end web solutions, collaborating across teams. Optimize performance, manage backend systems, and stay updated on trends.

As a Staff Machine Learning Scientist, you will focus on hiring and mentoring staff, raising technical standards, and applying machine learning to improve customer experiences. You'll research algorithms, conduct data analysis, and collaborate with teams to produce ML products.

The Staff Product Engineer will build AI-powered products, collaborate with ML scientists, contribute to software development phases, and mentor other engineers.

As Engineering Manager, you will lead a hands-on team building AI infrastructure, improving developer experience, and supporting ML teams while also contributing to production code.

The Engineering Manager will lead the AI Platform Team, overseeing infrastructure development, hands-on coding, and supporting ML teams while planning high-impact roadmaps and improving developer experience.

As a Forward Deployed Software Engineer, you will work with customers to implement AI solutions, guide product direction, and ensure successful technology adoption.

The AI Infrastructure Engineer will build and optimize training pipelines and inference services for AI models, enhance GPU-level performance, and mentor team members.

Build and operate GTM data systems covering account identity resolution, deduplication, corporate hierarchies, account and contact sourcing, enrichment, and Salesforce synchronization. Develop LLM-powered web research and enrichment pipelines, model data in dbt on Snowflake, orchestrate workflows with Airflow, and maintain quality controls. Partner closely with Sales, Marketing, RevOps, Partnerships, and Finance to create reliable data foundations that improve targeting, pipeline management, and revenue growth.

Design and implement AI-powered internal tools for GTM use cases, managing full lifecycle from data modeling to production. Collaborate closely with GTM teams to translate data into actionable insights with a focus on measurable business impact.