Senior Python Engineer — GenAI Platform

Westfield • Westfield Center, OH

133d

About The Position

Westfield is seeking a Python Engineer to build and harden the runtimes, services, and tooling that power our enterprise GenAI platform. This is a backend/platform engineering role. As part of our GenAI team, you’ll build APIs and agent operational frameworks, wire in observability and guardrails, enable systems to manage prompt/agent lifecycle, and achieve deploy on demand / release on demand practices at scale. You’ll partner with DevSecOps, security, and application teams to make LLM-based agents and prompt workflows reliable, compliant, and fast. Finally, you’ll aid in the operation of the platform, participating in monitoring and troubleshooting of the services you own.

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.

Nice To Haves

• Experience with agent frameworks (e.g. LangGraph, Pydantic AI, or similar) and prompt/agent workflow orchestration.
• Familiarity with prompt lifecycle management tools/patterns and automated LLM evals (quality/safety/regression).
• Knowledge of vector search and caching patterns (e.g., pgvector, Redis, Elasticsearch) and async tasking (e.g. Celery, Redis Queue).
• Infra-as-code (e.g. Terraform, Helm), container build/publish pipelines, and secure supply chain practices.
• Exposure to operational monitoring/debugging tools (e.g. Dynatrace, Graylog) feature flag platforms, and secret management.
• Understanding of DORA4 metrics with examples of improving lead time, deployment frequency, MTTR, and change failure rate.
• Experience with uv for Python dependency/build management; familiarity with uvicorn (ASGI) is a plus.

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.
• Add tracing/metrics/logging via our enterprise tools and monitoring infrastructure to create actionable dashboards/alerts.
• Keep linters and code scan reports clean; enforce RBAC, audit trails, data-access policies, PII controls, and prompt-injection defenses.
• Help own Azure DevOps YAML pipelines (pipeline-as-code) to enable deploy on demand; use feature flags and other techniques for release on demand.
• Drive a culture of fast unit tests, contract tests, and performance tests; keep coverage meaningful and PR checks green.
• Manage Python envs and builds with uv and containerization.
• Produce runbooks, reference implementations, and developer guides; mentor teams on how to use the platform.

What This Job Offers

• Number of Employees: 1,001-5,000 employees