Maisa builds an agentic automation platform designed to handle decision-heavy processes where hallucinations carry real cost—compliance, finance, legal intake, onboarding. The tech stack reveals a mature infrastructure play: Kubernetes, Terraform, Pulumi, Kafka, comprehensive observability (Grafana, Prometheus, Elasticsearch, Splunk), and security-first design (GuardDuty, CloudTrail, MITRE ATT&CK, SAML/OIDC). The hiring mix is entirely engineering-focused (senior + mid-level), with velocity accelerating—consistent with a startup still building the core platform rather than scaling sales, and the pain-point cluster (test flakiness, reliability in regulated environments, scaling quality) matches their active work on observability and incident response.
Maisa is a San Francisco-based startup (founded 2024) building an agentic process automation platform for enterprises. The product targets complex, exception-heavy workflows in finance, compliance, legal, and onboarding—processes where traditional RPA and general-purpose GenAI both fall short. The platform combines AI-driven reasoning with deterministic execution to ensure every action is auditable and reliable. Maisa currently operates as a 11–50 person team with 7 open engineering roles spanning senior and mid-level positions, hiring in Spain. The focus on cloud infrastructure automation, observability, security monitoring, and digital-worker design reflects a platform still in active construction.
Maisa runs on AWS with Kubernetes and Terraform/Pulumi for infrastructure. Core stack includes Kafka, Playwright/Cypress/Selenium for automation, Python/Go/JavaScript for logic, and Grafana/Prometheus/Elasticsearch for observability. Security tooling includes GuardDuty, CloudTrail, and MITRE ATT&CK integrations.
Active projects include cloud infrastructure automation, observability implementation, incident response, security monitoring at scale, and design of reusable digital-worker templates. Quality and reliability in regulated environments are core focus areas.
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