Backend Engineer
Rushdown Studios
AWSAzureCloudGoGoogle Cloud PlatformJavaKotlin.NETRustUnity
Senior Python Engineer, GenAI Platform
Westfield Health
full-time
Posted on:
Location Type: Hybrid
Location: Westfield Center • Ohio • 🇺🇸 United States
Visit company websiteJob Level
Senior
Tech Stack
AzureElasticSearchFlaskKubernetesMicroservicesOpenShiftPythonRedisTerraform
About the role
- Build Python services & SDKs that expose LLM/agent capabilities to internal teams and operate them on Kubernetes/OpenShift
- Support agent runtimes & workflows by implementing and managing operational workflows around AI technologies (e.g. LangGraph, OpenAI Agent SDK, MCP)
- Develop a cohesive enterprise GenAI platform for use cases across core insurance workflows and back office assistants
- Own platform reliability, scalability, performance, and cost
- Implement observability: add tracing, metrics, logging via enterprise tools and monitoring infrastructure; create actionable dashboards/alerts
- Implement security & governance: enforce RBAC, audit trails, data-access policies, PII controls, and prompt-injection defenses; keep linters and code scan reports clean
- CI/CD at scale: help own Azure DevOps YAML pipelines (pipeline-as-code) to enable deploy on demand; use feature flags for release on demand
- Drive testing culture: fast unit tests, contract tests, performance tests; maintain meaningful coverage and PR checks
- Manage dependency & packaging hygiene: manage Python envs and builds with uv and containerization
- Produce runbooks, reference implementations, developer guides; mentor teams on using the platform; participate in monitoring and troubleshooting of owned services
Requirements
- 4+ years of software engineering experience, including building backend services in Python (e.g. FastAPI, Flask)
- Demonstrated understanding of common software patterns and when to apply them
- Demonstrated experience running microservices and/or containerized deployments in production (Kubernetes/OpenShift)
- Hands-on experience with production logging, metrics, and tracing
- Experience satisfying automated code quality checks (e.g. SonarQube, Snyk)
- Solid understanding of Git workflows, code reviews, feature flags, and trunk-based development
- Comfortable with platform governance concepts like audit logging, RBAC, data privacy boundaries, and change control
- Comfort with AI Coding Assistants like GitHub Copilot or Claude Code in day-to-day work
- Strong testing discipline (e.g. pyunit/unittest, pytest), mocking, and CI gating
- Preferred: experience with agent frameworks (e.g. LangGraph, Pydantic AI) and prompt/agent orchestration
- Preferred: familiarity with prompt lifecycle management tools and automated LLM evals
- Preferred: knowledge of vector search and caching (pgvector, Redis, Elasticsearch) and async tasking (Celery, RQ)
- Preferred: infra-as-code (Terraform, Helm), container build/publish pipelines, and secure supply chain practices
- Preferred: exposure to monitoring/debugging tools (Dynatrace, Graylog), feature flag platforms, and secret management
- Preferred: understanding of DORA4 metrics and examples of improving lead time, deployment frequency, MTTR, change failure rate
- Preferred: experience with uv for Python dependency/build management; familiarity with uvicorn (ASGI)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonFastAPIFlaskKubernetesOpenShiftCI/CDunit testscontract testsperformance testsdependency management
Soft skills
mentoringtroubleshootingtesting disciplinecommunicationcollaboration