Integration Engineer – MANUS AI Platform

Integration Engineer – MANUS AI Platform

Location
: [Remote / Hybrid / On site, e.g., SFO Bay Area, CA]

Stage
:
Critical

Employment Type
:
Full Time

About the Role

We are looking for Integration Engineers to design, build, and maintain robust integrations between our internal systems (e.g., CRM, HRIS, data platforms, internal tools) and MANUS AI. You will own end-to-end integration workflows, including API design, data mapping, security, monitoring, and documentation, ensuring seamless and scalable automation across the organization.

Key Responsibilities

• Design and implement API-driven integrations between MANUS AI and internal platforms (e.g., Salesforce, Hub Spot, internal data warehouses, HR systems, ticketing tools).
• Develop and maintain webhooks, event-driven pipelines, and batch data flows to synchronize data between MANUS and downstream systems.
• Define and document integration architecture, data models, error handling strategies, and retry mechanisms for reliability and observability.
• Configure authentication, authorization, and secrets management (OAuth, API keys, SSO, environment variables) for secure access to MANUS and partner systems.
• Collaborate with product, data, security, and operations teams to align integration requirements with business workflows and compliance needs.
• Write clean, testable code and create automated tests, monitoring alerts, and runbooks for production-grade integrations.
• Troubleshoot integration issues, perform root cause analysis, and provide L2/L3 support for integration-related incidents.
• Maintain technical documentation, architecture diagrams, and integration playbooks for engineers and support teams.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent professional experience.
• 3–5+ years of experience as a Software Engineer, Integration Engineer, or Backend Engineer building production systems.
• Strong experience with RESTful APIs, webhooks, and event-driven architectures.
• Proficiency in at least one backend language (e.g., Python, Node.js, Java, Go) and modern frameworks.
• Experience with cloud platforms (AWS, GCP, or Azure) and related services (queues, storage, serverless, etc.).
• Familiarity with CI/CD pipelines, Git, and infrastructure as code (e.g., Terraform, Cloud Formation).
• Understanding of security best practices, including API security, secrets management, and compliance (e.g., SOC 2, GDPR).
• Strong problem-solving skills, ability to work independently, and collaborate effectively with cross-functional teams.

Preferred Qualifications

• Experience integrating AI / LLM platforms or workflow automation tools (e.g., AI agents, RPA, no-code automation).
• Familiarity with data modeling, ETL/ELT pipelines, and data warehouse concepts (e.g., Snowflake, Big Query, Redshift).
• Experience with observability tools (e.g., Datadog, Prometheus, Grafana, logging platforms).
• Exposure to SaaS platforms (e.g., Salesforce, Hub Spot, Workday, Service Now) and their APIs.
• Interest in AI-driven automation, workflow orchestration, and “action engine” style platforms like MANUS.