Growth Engineer (AI)

Location: Remote in Mexico

Company

hirify.global provides AI-powered identity verification and security solutions for banks, fintechs, marketplaces, governments, retail, hospitality, and gaming companies.

What you will do

• Design, build, deploy, and maintain production LLM agents for outbound, inbound, lead qualification, routing, event, and competitive-research workflows.
• Build and operate MCP servers and clients integrating Salesforce, HubSpot, Outreach, Supabase, ZoomInfo, Notion, and Slack, including authentication, token scoping, pagination, rate limiting, and graceful failure handling.
• Implement grounding, schema-aware retrieval, reconciliation checks, evaluation harnesses, regression tests, and versioned prompt and skill artifacts.
• Build workflow automation with webhooks, scheduled jobs, event-driven pipelines, queues, retries, idempotency, backfills, routing, scoring, and decision logic.
• Create internal web applications, dashboards, and interactive reporting for BDRs and revenue leadership.
• Document architecture, skills, and runbooks so GTM operators and other engineers can maintain and extend the agent fleet.

Requirements

• 4+ years of professional software engineering experience and 1+ year building and shipping LLM-powered applications or agents to production for daily use by non-engineers.
• Strong production Python and Node.js/TypeScript skills, with enough React experience to build internal user interfaces end to end.
• Experience building at least one internal application from data model and backend through interface, authentication, deployment, and ongoing maintenance.
• Hands-on experience with both Salesforce and HubSpot, including standard and custom objects, field behavior and validation, ownership and sharing, REST and bulk APIs, and downstream data effects.
• Experience with Outreach, Salesloft, or Apollo, including sequences, steps, prospect and mailing data structures, and API access patterns.
• Practical understanding of revenue-data quality issues such as duplicates, stale ownership, unenforced picklists, and partially migrated fields.
• Production experience with Postgres or Supabase, including schema design, migrations, indexing, query tuning, and row-level security; SQL fluency with Redshift, Snowflake, or BigQuery-class warehouses, including window functions and incremental models.
• Experience reconciling the same metric across two systems, identifying the difference, and explaining it to a non-technical stakeholder.
• Experience designing, building, deploying, monitoring, and maintaining production automations, including alerting and failure-mode ownership; experience with webhooks, queues, scheduled jobs, retries, idempotency, and backfills.
• Experience with n8n, Tines, Zapier, or similar automation platforms and the judgment to replace them with custom services when appropriate.
• Experience implementing routing, scoring, and decision logic as tested code.
• Hands-on experience with MCP servers, clients, custom endpoints, or an equivalent tool-calling and agent framework.
• Production LLM API integration experience, including structured output, tool definitions, context management, and cost and latency trade-offs.
• Experience treating prompts and agent skills as versioned artifacts and evaluating their impact.
• Cloud deployment ownership with AWS, containerized hosting, and CI/CD using GitHub Actions; experience with OAuth flows, token lifecycle and refresh, credential vaults, header authentication, and least-privilege access review.

Nice to have

• Terraform or another infrastructure-as-code tool.
• Experience supporting multi-region revenue teams across NAM, LATAM, and EMEA, including data-residency considerations.
• Event and conference lead-capture tooling.
• Notion and Slack API experience.
• Experience enabling non-technical teams to use AI tooling through documentation, training, and internal adoption.

Culture & Benefits

• Flexible working hours and workplace.
• Open vacation policy.
• High-performance culture with freedom and responsibility, context rather than control, and highly aligned, loosely coupled teams.
• Continuous feedback, promotions, and development opportunities.
• Ownership and autonomy within a global AI identity-solutions company.

Hiring process

• Be prepared to discuss two or three shipped projects, including internal applications, integrations, agents or automations, data reconciliations, and documented handoffs.
• Evaluation focuses on shipped outcomes, failure handling, and measurable before-and-after impact rather than the specific tools used.