HeyStranger AI is an autonomous AI-powered sales-development platform that helps businesses generate qualified meetings through personalized outbound outreach. It combines AI agents, lead intelligence, prospect research, and multichannel campaign automation to handle work traditionally performed by SDR teams.
As a Senior Full-Stack Engineer, I worked on AI infrastructure, lead-enrichment pipelines, outreach automation, campaign management, and analytics dashboards. My work spanned frontend and backend systems designed to preserve personalization quality across thousands of outreach activities.
The product challenge
The platform needed to automate research, personalization, and campaign execution at scale without producing generic, template-like outreach. It also needed reliable workflows for processing lead data, managing campaign state, and giving users a clear view of engagement.
What I built
AI agent and personalization workflows
I developed systems that enabled AI agents to analyze prospect information, research companies and decision-makers, generate personalized outreach, adapt messaging to prospect profiles, build dynamic follow-up sequences, and improve messaging based on engagement data. Prompt engineering and workflow orchestration helped keep generated communications relevant and consistent.
Lead intelligence and enrichment
I built enrichment pipelines that aggregated information from multiple sources to create richer prospect profiles. The workflows covered company intelligence, contact enrichment, social-profile analysis, industry classification, lead scoring, and prospect segmentation.
Outreach automation engine
I developed infrastructure for automated cold-email campaigns, multi-step follow-ups, scheduling and delivery workflows, reply tracking, campaign-state management, and engagement monitoring. Backend orchestration allowed users to launch and manage outbound campaigns at scale.
Campaign management and analytics
I built user-facing tools for creating campaigns, managing prospect lists, configuring AI-personalization settings, reviewing generated outreach, and monitoring campaign performance. Reporting dashboards surfaced delivery performance, open and reply rates, conversion metrics, campaign effectiveness, and lead-engagement trends.
Backend architecture and processing
I designed and developed backend services for user management, campaign orchestration, AI workflow execution, lead processing, analytics aggregation, and third-party integrations. Asynchronous and queue-based processing supported high-volume outreach operations.
Outcome
The work helped establish an AI SDR platform that reduced manual prospect research and personalization through AI-driven workflows. It delivered scalable lead-enrichment, campaign-orchestration, and analytics systems that support high-volume prospecting and engagement.