Principal, AI Platform Engineer

NRG

3d•Onsite

About The Position

We are seeking a Principal AI Platform Engineer to build the shared product-integrity layer for customer-facing AI systems. This role will create the evaluation, observability, safety, and launch-readiness infrastructure needed to ship AI features with measurable quality, reliability, and customer impact. In this role, you will be responsible to: Build shared evaluation infrastructure for models, prompts, agents, and multimodal AI systems. Own golden datasets, regression suites, offline and online evals, and LLM-as-judge governance. Develop observability for model quality, latency, cost, drift, safety, and customer impact. Create launch-readiness gates for AI features across camera, agentic, personalization, multimodal, and energy products. Partner with Product, Analytics, Privacy, Security, and Engineering on trustworthy AI productization. Define reusable standards for AI quality, monitoring, safety, and operational readiness.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field
10+ years of software engineering, ML engineering, or AI platform experience
Experience evaluating, deploying, or monitoring production AI systems
Strong Python and data engineering skills
Experience with offline/online evaluation, data quality, model monitoring, or observability systems
Familiarity with LLM evaluation, prompt evaluation, model regression testing, or safety guardrails
Strong communication skills and ability to set standards across teams

Nice To Haves

Experience with LLM-as-judge, agent tracing, multimodal evals, golden datasets, or automated regression suites
Experience with GCP/AWS, Vertex AI, SageMaker, MLflow, Datadog, OpenTelemetry, Private Cloud or similar tooling
Experience with privacy-aware AI systems, customer trust metrics, or launch-readiness processes
Experience supporting computer vision, GenAI, recommendation, or edge AI products
Experience building developer platforms or internal AI tooling

Responsibilities

Build shared evaluation infrastructure for models, prompts, agents, and multimodal AI systems.
Own golden datasets, regression suites, offline and online evals, and LLM-as-judge governance.
Develop observability for model quality, latency, cost, drift, safety, and customer impact.
Create launch-readiness gates for AI features across camera, agentic, personalization, multimodal, and energy products.
Partner with Product, Analytics, Privacy, Security, and Engineering on trustworthy AI productization.
Define reusable standards for AI quality, monitoring, safety, and operational readiness.