Sr. AI Platform Integration Engineer
New
United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- DockerPythonFlaskKubernetesFastAPIGoRESTful APIs
Requirements
- 5+ years of backend or integration engineering experience in production environments.
- Strong experience building services in Python (e.g., FastAPI, Flask) or Go.
- Proven experience designing and operating enterprise-grade APIs and distributed integration systems.
- Deep understanding of authentication/authorization systems, including RBAC, multi-tenant architectures, and security best practices.
- Hands-on experience with SAML 2.0 and OIDC-based SSO integrations, including identity providers like Okta, Azure AD, or Ping Identity.
- Strong knowledge of API security, schema validation, and distributed system integration patterns.
- Experience working with Docker, Kubernetes, Git, and modern CI/CD pipelines.
- Familiarity with technical design reviews, RFCs, and engineering documentation practices.
- Exposure to observability, platform engineering, or AIOps environments is highly desirable.
- Strong communication skills and ability to collaborate across multiple engineering teams in fast-paced environments.
Responsibilities
- Design and implement scalable RESTful APIs and integration services that enable AI-driven automation and cross-system connectivity across a distributed platform.
- Define and evolve integration standards, including authentication, versioning, schema contracts, and access control for internal and external services.
- Build and maintain secure authentication and authorization systems, including token-based access (JWT/OAuth 2.0) and fine-grained endpoint-level controls.
- Contribute to RBAC architecture and policy enforcement models supporting multi-tenant access and enterprise-grade security.
- Support enterprise identity integrations using SAML 2.0 and OpenID Connect (OIDC), including providers such as Okta, Azure AD, and Ping Identity.
- Partner with infrastructure, platform, and data engineering teams to align API contracts, data semantics, and integration patterns.
- Implement observability, audit logging, and traceability for authentication, authorization, and system-level activity across services.
- Design and maintain containerized services deployed on Kubernetes with secure configuration and secrets management practices.
- Participate in architecture discussions, code reviews, and technical documentation efforts (RFCs, ADRs).
- Mentor engineers and contribute to engineering best practices across the broader platform organization.
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