Hybrid AI Engineer

at Westfield Health

• Job title: AI Engineer
• Job type: Full Time
• Experience level: Junior, Mid level
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Azure, Docker, Kubernetes, OpenShift, Python
• Location requirements: Hybrid, Westfield Center, United States

About the role

• AI Engineer at Westfield developing AI use cases impacting insurance workflows. Collaborating with engineers and stakeholders to implement diverse AI features.

Responsibilities

• Build containerized AI services in Python. Implement clean APIs where needed and standards-based integrations for enterprise systems.
• Design retrieval & agent flows using industry-standard frameworks; implement prompt/tool versioning and safe rollouts (e.g., feature flags, canary).
• Guardrails & governance: help implement controls around PII handling, audit logging, RBAC, prompt-injection defenses, and egress controls.
• Evaluation automation: create eval harnesses, golden sets, regression gates, and basic business KPIs (e.g., quality, safety, latency, cost).
• Observability: instrument tracing/metrics/logging with standard tooling, integrate with enterprise monitoring/logging platforms, and build actionable dashboards/alerts.
• Operational rigor: contribute to runbooks and incident hygiene. Participate in the on-call rotation for the AI services you help own.
• CI/CD: use pipeline-as-code for delivery and keep code-quality/security gates clean for frequent deployments.
• Team play: embed with asset teams when appropriate. Contribute back reusable components, SDKs, and docs to the AI engineering platform.

Requirements

• At least 2 years of software engineering experience, including at least 1 production-deployed GenAI use case for real business users or consumers.
• Strong Python and microservice fundamentals (e.g., FastAPI or similar, type hints, tests such as pytest) with an emphasis on well-structured, readable code.
• Hands-on experience with any AI orchestration frameworks (e.g., LangChain, LangGraph, OpenAI Agents SDK, PydanticAI or similar).
• Containers/orchestration experience: solid containerization understanding and hands-on with deploy/scale/config/secret management (e.g., Docker, Kubernetes/OpenShift).
• Observability experience: metrics, logs, tracing (e.g., OTel) and using these signals to debug production outages and performance issues.
• CI/CD discipline (e.g., Azure DevOps YAML or similar), code-quality/security gates (e.g., SonarQube, Snyk), and dependency management basics.
• Governance understanding: audit logs, RBAC, data-privacy boundaries, and change control in business-critical environments.

Benefits

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