• Design and build AI-driven features for our domain services platform using Python and Golang. • Integrate and fine-tune open-source models with cutting-edge architectures via tools like Ollama. • Research, evaluate, and implement emerging AI technologies that align with our vision for smarter, more intuitive products and services. • Collaborate with internal stakeholders and fellow engineers to rapidly prototype and iterate on machine learning and LLM-based features. • Contribute to a modern AI development stack, ensuring scalability, performance, and ethical usage of models. • Actively participate in the open-source ecosystem and bring relevant tools and techniques back to the team. • Implement software solutions with “intelligent” features, helping teams automate tedious and repetitive tasks.

• Design and implement scalable AI-driven features • Own the full lifecycle of AI services • Write clean, maintainable code primarily in Python • Establish standards for data privacy, model bias, and security

• Play a critical role in expanding product offerings across the tech stack • Analyze tough customer problems and design efficient backend solutions • Design, develop, and maintain scalable systems and features • Work with business team to build user stories from requirements

• Build end-to-end GTM workflows across targeting, enrichment, scoring, routing, sequencing, and reporting • Reduce manual work while improving speed, consistency, and data quality • Implement ICP rules, intent signals, and decision logic that hold up at scale • Connect Hubspot, Salesforce, enrichment tools, outbound platforms, and automation into a single operating system • Ensure GTM execution scales without breaking deliverability or data integrity • Build dashboards that surface funnel health, lead quality, and pipeline performance, and identify where leads drop off so you can fix the system, not the symptom • Translate business requirements into technical workflows across Marketing, SDR, Sales, RevOps, and CS • Create scripts or automations when off-the-shelf tools fall short, debug broken workflows and integration issues, and maintain clean documentation so systems scale beyond you