AI Engineer - Monitoring, Observability, and Governance
About The Position
This role is responsible for engineering and operating third-party applications within an on-premises OpenShift environment supporting enterprise GenAI monitoring, observability, and governance. The position will develop and integrate application components, deploy and support containerized services, and maintain AI guardrail and observability platforms such as Galileo and LangSmith. The engineer will monitor application quality, safety, and performance while helping operationalize model-based evaluation workflows and supporting enterprise AI governance initiatives. The domain is GenAI operations: the applications you run provide guardrails and observability for LLM- and RAG-powered systems across the enterprise. You will work with these vendor tools to monitor application quality, safety, and performance—tracking metrics such as attribution, grounding, prompt-injection detection, tone, bias, and PII handling—and surface them through dashboards and alerting. Where the platform uses model-based evaluation (LLMs-as-Judges and specialized/small language models), you will help operationalize, calibrate, and maintain those workflows. Because the AI landscape changes quickly, the ideal engineer learns new tools and environments fast, brings a pragmatic build-and-operate mindset, and can lead cross-functional work to move initiatives forward.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, MIS, related field, or equivalent experience.
- 10+ years of software engineering experience designing, building, and scaling production applications.
- Strong Python development experience, including data and machine learning libraries.
- Experience deploying and supporting containerized workloads on OpenShift or Kubernetes.
- Experience taking LLM or RAG-based applications into production.
- Understanding of AI risks, agent behavior, and governance frameworks.
- Experience building APIs and integrating third-party platforms.
- Experience with OpenAI APIs and orchestration frameworks such as LangChain.
- Understanding of inference performance optimization and observability.
- Experience implementing AI guardrails and model-based evaluation frameworks.
- Experience working in Agile environments.
- Demonstrated technical leadership and stakeholder influence.
Nice To Haves
- Experience delivering technology solutions in large, complex, regulated organizations, preferably financial services.
- Experience with annotation pipelines, feedback loops, fine-tuning, and alignment techniques.
- Familiarity with prompt versioning and lifecycle management.
- Experience with Galileo, LangSmith, Splunk, or similar observability platforms.
- Knowledge of additional GenAI frameworks such as LlamaIndex or Haystack.
- Experience supporting evaluation and guardrails for agentic AI workflows.
- Strong collaboration skills and ability to quickly learn emerging technologies.
Responsibilities
- Develop, deploy, and support vendor applications in a fully on-premises OpenShift environment.
- Build APIs and integrations connecting guardrail and observability tools with enterprise GenAI applications.
- Implement and maintain operational monitoring for application performance, safety, latency, and quality metrics.
- Develop and calibrate model-based evaluation workflows including annotation and feedback processes.
- Utilize orchestration frameworks such as LangChain for guardrails, prompt management, and scoring workflows.
- Create observability dashboards and alerting capabilities.
- Troubleshoot production issues and improve scalability, reliability, and performance.
- Support emerging agentic and multi-step AI workflows.
- Lead and mentor team members while driving engineering standards and cross-functional delivery.
Benefits
- Access to paid time off
- Resources and support to our employees
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What This Job Offers
Job Type
Full-time
Career Level
Senior
