Senior AI Platform Engineer

CareBridge-posted 3 months ago
$152,680 - $249,840/Yr
Full-time • Senior
Chicago, IL
251-500 employees
Ambulatory Health Care Services
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The Senior AI Platform Engineer will design, build, and operate production AI systems that power platform experiences: RAG pipelines, model endpoints, evaluation harnesses, guardrails, and multi-tenant AI services published through a developer hub/marketplace.

  • Lead end to end AI solutioning: problem framing, data sourcing, labeling strategy, model/LLM selection, and safety considerations.
  • Build retrieval augmented generation and agentic workflows: document processing, chunking/embedding strategies, vector indexing, prompt/chain design, tool use, and guardrails (content filters, policy enforcement).
  • Implement evaluation with golden datasets, automatic metrics, rubric based grading, and human in the loop reviews; run A/B and interleaving tests.
  • Productionize inference (synchronous, batch, streaming) with autoscaling, caching, request routing/fallbacks, cost and token/latency budgets, and kill switch patterns.
  • Establish LLMOps/MLOps foundations: experiment tracking, model registry, data/model lineage, governance, CI/CD for models/prompts, and safe rollback.
  • Instrument AI observability (prompt traces, quality drift, hallucination/safety events, per tenant cost dashboards); drive continual improvement cycles.
  • Partner with platform engineers to expose AI capabilities as APIs/SDKs, publish to the marketplace with metadata, versioning, and deprecation policies.
  • Collaborate with security, privacy, and risk on data minimization, access controls, PII handling, and policy aligned evaluation, document tradeoffs and decisions.
  • Mentor engineers and data scientists; create reusable evaluation harnesses, prompt libraries, and templates that accelerate feature delivery.
  • Requires a Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree and 6 or more years of experience; or any combination of education and experience in configuration management, which would provide an equivalent background.
  • Strong Python plus one systems language; experience with model serving (batch/online), GPU utilization, and optimization (quantization, distillation).
  • Practical knowledge of vector databases, embedding generation, prompt/chain orchestration, and evaluation methodologies for generative systems.
  • Experience integrating with feature stores, catalogs/registries, and data governance controls in cloud environments.
  • Familiarity with responsible AI topics (safety, privacy, bias) and how to operationalize them in production.
  • Comprehensive benefits package
  • Incentive and recognition programs
  • Equity stock purchase
  • 401k contribution
  • Paid Time Off
  • Medical, dental, vision benefits
  • Short and long term disability benefits
  • Life insurance
  • Wellness programs
  • Financial education resources
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