Description :

You will build the data backbone that connects our platform to every tool account managers rely on. AI agents are only as good as their context you will ensure our agents have access to complete, real-time client data across all platforms.

This is a high-ownership, high-impact role. You will not be handed tickets. You will identify the integration gaps that limit our agents, design the solutions, and ship them end-to-end from database schema through to the UI. You will also work closely with clients to understand their tech environments and build integrations that fit seamlessly into how they work.

Without robust integrations, the entire product vision fails. This role is foundational to everything Kaizan delivers.

What You'll Build in 2026 :

- CRM integrations Salesforce, HubSpot, Pipedrive with bidirectional real-time data sync so agents always have the latest client records

- Project management integrations Asana, Jira, Monday.com enabling agents to track deliverables and surface risks tied to live work

- Chat and communication integrations Slack, Microsoft Teams, Gmail so every client conversation flows into Kaizan's context layer

- Document system integrations Google Drive, SharePoint, Notion for document processing pipelines that feed AI agent context

- Real-time data sync infrastructure including webhook listeners, event queues, and retry logic to ensure zero data loss

- OAuth 2.0 apps and marketplace listings on Salesforce AppExchange, Slack App Directory, and Google Workspace Marketplace

- MCP (Model Context Protocol) integrations and the Kaizan MCP server, enabling clients to connect Kaizan's intelligence layer directly into their own AI tooling

- Integration health monitoring and observability dashboards so the team can detect and resolve sync failures before clients notice them

Key Responsibilities :

- Own the full integration lifecycle : scoping, architecture, development, testing, deployment, and ongoing maintenance

- Design robust, scalable data schemas that support multi-tenant architectures and handle high-volume event streams

- Build and maintain RESTful and GraphQL APIs that expose integration data to Kaizan's AI agent layer

- Implement and manage OAuth flows, API key management, and secure credential storage across all third-party platforms

- Work directly with enterprise clients to understand their existing tech stacks and build custom integration configurations

- Collaborate with the AI architecture team to define the data contracts and schemas agents need to function effectively

- Write clean, well-tested, production-grade code you set the bar for integration quality across the team

- Contribute to technical documentation, runbooks, and integration guides for both internal teams and external developers

Tech Stack :

- Backend : Node.js or Python (FastAPI / Express), PostgreSQL, Redis

- Frontend : React, TypeScript comfortable building lightweight UI for integration configuration flows

- APIs : REST, GraphQL, webhooks, OAuth 2.0, OpenAPI / Swagger

- Infrastructure : AWS or GCP, Docker, Kubernetes, CI/CD pipelines

- Data : event queues (Kafka, SQS, or equivalent), ETL pipelines, data transformation layers

- Observability : Datadog, Sentry, or equivalent monitoring and alerting tooling

Who We're Looking For :

Experience : 5-8 years in full-stack engineering

- Deep hands-on experience building and owning third-party API integrations at production scale not just consuming APIs, but architecting integration systems

- Proven track record of shipping integrations with CRMs, project management tools, or enterprise SaaS platforms

- Comfortable owning features end-to-end : from database design through API development to frontend UI

- Strong understanding of webhook architectures, event-driven data sync, and how to handle eventual consistency at scale

- Experience with OAuth 2.0 flows, marketplace app submissions, and third-party API rate limit management

- Security-conscious mindset you think about credential storage, data isolation, and least-privilege access by default

- Excellent written and verbal communication you can explain integration architecture to a non-technical client as clearly as to an engineer

Nice to Have :

- Experience building or contributing to MCP servers or similar AI context protocols

- Familiarity with document processing pipelines parsing PDFs, extracting structured data from unstructured documents

- Prior work at a B2B SaaS company where integrations were a core product surface

- Experience with multi-tenant SaaS architecture and enterprise data isolation requirements

- Contributions to open-source integration libraries or published marketplace apps