Sr. Python Developer - Cloud Platform Engineering

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 a small set of platform planes - an AI Control Plane that acts as the single enforcement point for identity, policy, and routing; a Data Plane of governed retrieval and query services; an Observability Plane; and a Developer Plane. Every AI request in the enterprise flows through this platform. You will design and ship the Python services that make that possible: gateway and policy enforcement components, retrieval and orchestration services, event-driven integration between planes, and the audit and telemetry surfaces that make the platform trustworthy in a compliance-sensitive environment. This is a builder role. This resource will own services end to end - API contracts, implementation, tests, deployment pipelines, and production operation on Azure - and will work across service boundaries owned by other teams, which means clear written communication and disciplined, versioned interfaces are part of the job, not an afterthought.

What this role will build and own: -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 so downstream clients and other teams can build against stable interfaces. -Build event-driven integration between platform components using Azure messaging services (Event Hubs, Service Bus) for async, decoupled communication. -Contribute to the platform's agent execution capabilities - tool-calling services, retrieval-augmented generation (RAG) pipelines, and the 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 done, not a follow-up task. -Document design tradeoffs and coordinate across service boundaries owned by other teams (data engineering, identity, application teams) in writing.

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 given our stack; 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: identity and access management (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.

Nice to Have Skills & Experience

-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, and prior exposure shortens the ramp considerably. -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 - for example, a control plane vs. data plane split, zero-trust patterns, or service-to-service authentication. -Exposure to data engineering pipelines: Azure Data Factory, Microsoft Fabric, Event Hubs ingestion, batch and streaming.

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.