Senior Applied AI Engineer
The Hartford
AWSAzureCloud
AI Engineer
Westfield Health
full-time
Posted on:
Location Type: Hybrid
Location: Westfield Center • Ohio • 🇺🇸 United States
Visit company websiteJob Level
JuniorMid-Level
Tech Stack
AzureDockerKubernetesOpenShiftPython
About the role
- 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.
- Experience deploying and supporting multiple custom GenAI use cases in production (preferred).
- Familiarity with MCP, A2A, or other AI integration standards (preferred).
- Experience with RAG and vector search (preferred).
- Experience with Python dependency/build management (e.g., uv) and familiarity with ASGI servers (e.g., uvicorn) (preferred).
Benefits
- Hybrid defined as three (3) or more days per week in the office.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonmicroservicesFastAPIAI orchestration frameworksDockerKubernetesobservabilityCI/CDRBACPython dependency management
Soft skills
team collaborationincident managementcommunicationproblem-solvingorganizational skills