AI Engineer - MCP Server Development | Senior

• Design and develop MCP servers in Python using the MCP SDK and established engineering frameworks.
• Define tool specifications, including tool sets, authentication requirements, rate limits, pagination, and data-handling rules.
• Build robust asynchronous API clients for enterprise SaaS and data platforms, including authentication, retries, backoff, rate limiting, pagination, and error handling.
• Design clear, model-friendly tool interfaces using Pydantic schemas and iterate based on LLM evaluation results.
• Integrate services with existing OAuth and authentication mechanisms, ensuring secure handling of credentials and secrets.
• Implement caching and quota-protection strategies for third-party APIs.
• Develop unit and integration tests using pytest, including testing against sandbox environments.
• Support security practices such as least-privilege access, audit logging, protection of write/destructive actions, and secure handling of untrusted data.
• Deploy and operate services on Kubernetes, working with Helm or Kustomize and established CI/CD pipelines.
• Configure and work with observability tools such as structured logging, metrics, and distributed tracing.
• Create technical specifications and documentation for the services you build.
• Collaborate with engineers and stakeholders to take integrations from design through production deployment.

• 5+ years of professional backend development experience, including at least 3 years working with Python.
• Strong experience with Python, asynchronous programming, typing, and Pydantic.
• Proven experience integrating third-party REST APIs in production, including authentication, pagination, rate limiting, webhooks, and error handling.
• Working knowledge of OAuth 2.0, including authorization flows, token refresh, and scopes.
• Hands-on experience deploying and operating services with Kubernetes, including containers, Helm or Kustomize, health probes, and basic autoscaling concepts.
• Experience working with CI/CD pipelines in a production environment.
• Strong testing practices with pytest, mocking, and integration testing.
• Experience with observability concepts and tools such as Prometheus, OpenTelemetry, structured logging, or equivalent technologies.
• Strong written communication skills and the ability to create clear technical specifications and documentation.

Nice to have

• Hands-on experience with MCP, LLM tool/function calling, AI agents, or AI integrations.
• Experience integrating enterprise platforms such as Salesforce, Jira/Atlassian, Snowflake, ServiceNow, Workday, or similar systems.
• Experience with Vault, External Secrets Operator, or other enterprise secrets-management solutions.
• Experience using Redis or similar technologies for caching.
• Familiarity with prompt-injection risks and secure patterns for LLM-facing applications.
• Experience working with enterprise security reviews and least-privilege access models.

• Competitive compensation paid in USD.
• 100% Remote.
• Paid Time Off: 12 PTO days per year.
• Local Holidays: All official holidays in your country.
• Birthday Off.
• Career Growth opportunities.
• Recognition Program.
• Paid approved leaves