Hybrid Senior Python Engineer – GenAI Platform

at Westfield Health

• Job title: Senior Python Engineer – GenAI Platform
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Azure, Flask, Kubernetes, Microservices, OpenShift, Python
• Location requirements: Hybrid, Westfield Center, United States

About the role

• Python Engineer responsible for building and managing services for GenAI platform. Collaborating with multiple teams to enhance platform reliability and functionality.

Responsibilities

• Build Python services & SDKs that expose LLM/agent capabilities to internal teams; 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, others).
• Develop a cohesive enterprise platform for GenAI use cases that run the gamut from core insurance workflows to back office assistants.
• Own platform reliability, scalability, performance, and cost.
• Observability: add tracing/metrics/logging via our enterprise tools and monitoring infrastructure to create actionable dashboards/alerts.
• Security & governance: keep linters and code scan reports clean; enforce RBAC, audit trails, data-access policies, PII controls, and prompt-injection defenses.
• CI/CD at scale: help own Azure DevOps YAML pipelines (pipeline-as-code) to enable deploy on demand; use feature flags and other techniques for release on demand.
• Testing culture: drive a culture of fast unit tests, contract tests, and performance tests; keep coverage meaningful and PR checks green.
• Dependency & packaging hygiene: manage Python envs and builds with uv and containerization.
• Docs & enablement: produce runbooks, reference implementations, and developer guides; mentor teams on how to use the platform.

Requirements

• 4+ years of software engineering experience, including building backend services in Python (e.g. FastAPI, Flask), with strong API design and production operations experience.
• Demonstrated understanding of common software patterns and when to apply them.
• Demonstrated experience running microservices and/or containerized deployments in production.
• 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 practices that enable deploy on demand / release on demand.
• Comfortable with platform governance concepts like audit logging, RBAC, data privacy boundaries, and change control in business-critical environments.
• 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.

Benefits

• Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.