AI Engineer

Job Summary

Westfield is hiring an AI Engineer to build AI use cases of various shapes and sizes that impact our core insurance workflows. You’ll work with other AI Engineers, software developers, and business stakeholders to ship features and assets ranging from simple prompt workflows and document understanding to AI agents, RAG, computer vision, and more. You’ll be involved in business use cases from design and architecture through implementation, testing, deployment, monitoring, and maintenance.

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

• Build containerized AI services in Python and implement clean APIs and standards‑based integrations for enterprise systems.
• Design retrieval and 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 evaluation 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 platforms, and build actionable dashboards/alerts.
• Operational rigor: contribute to runbooks and incident hygiene; participate in on‑call rotation for the AI services you 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, contributing reusable components, SDKs, and docs to the AI engineering platform.

• 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 (FastAPI or similar, type hints, tests such as pytest) with emphasis on well‑structured, readable code.
• Hands‑on experience with AI orchestration frameworks (Lang Chain, Lang Graph, OpenAI Agents SDK, Pydantic
  
  AI, or similar).
• Containerization and orchestration experience: solid containerization understanding and hands‑on with deploy/scale/config/secret management (Docker, Kubernetes/Open Shift).
• Observability experience: metrics, logs, tracing (OTel) and using signals to debug production outages and performance issues.
• CI/CD discipline (Azure Dev Ops YAML or similar), code‑quality/security gates (Sonar Qube, Snyk), and dependency management basics.
• Governance understanding: audit logs, RBAC, data‑privacy boundaries, and change control in business‑critical environments.

• Experience deploying and supporting multiple custom GenAI use cases in production.
• Familiarity with MCP, A2A, or other AI integration standards.
• Experience with RAG and vector search.
• Experience with Python dependency/build management (uv) and familiarity with ASGI servers (uvicorn).

Hybrid: three (3) or more days per week in the office.

• Collaborates
• Customer focus
• Communicates effectively
• Decision quality
• Nimble learning

United States:
All applicants receive consideration for employment without regard to race, color, sex, religion, national origin, age, sexual orientation, gender identity, disability, or status as a protected veteran. United Kingdom:
Westfield is committed to equality of opportunity for all staff and applications from individuals are encouraged regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships.