Sr. Python Developer - Cloud Platform Engineering

Overview Insight Global is seeking a Senior Python Developer to build the backend services that power the client's enterprise AI platform. This is a hands-on senior individual contributor role on the Platform Engineering team. The AI platform is organized around platform planes: an AI Control Plane (identity, policy, routing), a Data Plane (governed retrieval and query services), an Observability Plane, and a Developer Plane. Every AI request flows through this platform. You will design and ship Python services that enable gateway and policy enforcement, retrieval and orchestration, event-driven integration between planes, and audit and telemetry surfaces for a compliant, trustworthy platform. This is a builder role. You will own services end to end — API contracts, implementation, tests, deployment pipelines, and production operation on Azure — and work across service boundaries owned by other teams, requiring clear written communication and disciplined, versioned interfaces. Responsibilities Design, build, and operate production Python services (FastAPI/async) across the platform's Control Plane, Data Plane, and Observability Plane, including gateway integration, policy enforcement, retrieval APIs, and service-to-service orchestration. Implement and maintain governed API contracts (REST, OpenAPI/schema-first) at plane boundaries with backward-compatible versioning for stable downstream interfaces. Build event-driven integration between platform components using Azure messaging services (Event Hubs, Service Bus) for asynchronous, decoupled communication. Contribute to the platform's agent execution capabilities — tool-calling services, retrieval-augmented generation (RAG) pipelines, and evaluation harnesses that gate AI features before production. Enforce the platform's security model in code: managed identities and least-privilege RBAC, Key Vault-backed secrets, private endpoints and network segmentation, and metadata-only logging with no raw payload or PII leakage. Own deployment and operations for your services: Infrastructure-as-Code (Bicep/Terraform), CI/CD pipelines, containerized deployment on Azure Container Apps / AKS, and observability instrumentation (Application Insights, OpenTelemetry, KQL). Own test coverage for critical paths — unit and integration tests (pytest) are a condition of completion, not a follow-up task. Document design tradeoffs and coordinate across service boundaries owned by other teams (data engineering, identity, application teams) in writing. Qualifications 5–10 years of professional software development experience, with the majority in Python. Strong experience with a modern async Python web framework; FastAPI strongly preferred; Flask/Django acceptable with a willingness to ramp quickly on FastAPI and async patterns. Hands-on production experience with a major public cloud; Azure strongly preferred; strong AWS/GCP candidates can transfer but should expect an Azure ramp-up. Practical experience with containerized services (Docker) and orchestration on a managed platform (Azure Container Apps, AKS, ECS, Cloud Run, or similar). Solid grounding in cloud security fundamentals: IAM (RBAC, managed identities / service principals), secrets management (Key Vault or equivalent), network segmentation (VNets, private endpoints / Private Link), and the principle of least privilege. Experience with message/event systems (Event Hubs, Service Bus, Kafka, SQS/SNS, or similar) for asynchronous, decoupled service communication. Comfortable working with Infrastructure-as-Code (Bicep, Terraform, or CloudFormation) and CI/CD pipelines. Strong API design skills (REST, OpenAPI / schema-first contracts) and experience maintaining backward-compatible, versioned APIs across service boundaries. Testing discipline: unit and integration testing with pytest or equivalent, and comfort owning test coverage for critical paths. Clear written and verbal communication — this role documents tradeoffs and coordinates across service boundaries owned by different teams. Experience with Azure AI Search, vector/hybrid search, or embedding pipelines. Experience with Azure OpenAI or other LLM/agent-oriented systems — tool-calling, RAG, evaluation harnesses. This platform is building toward an agent execution engine; prior exposure shortens ramp time. Experience in regulated or compliance-sensitive environments: data governance, audit logging, PII/sensitive-data handling, and audit-before-action patterns. Familiarity with observability tooling: KQL, Azure Monitor / Application Insights, Grafana, OpenTelemetry. Experience designing systems with explicit trust boundaries — e.g., control plane vs data plane, zero-trust patterns, or service-to-service authentication. Exposure to data engineering pipelines: Azure Data Factory, Microsoft Fabric, Event Hubs ingestion, batch and streaming. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. 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