Openreqstaffing

Openreqstaffing

SuperDial - Applied AI

San Francisco, USA

Sponsorship not specifiedDetected 82 days ago
TypeScriptPythonJavaGoDistributed SystemsFull-Stack DevelopmentVector DatabasesAWSGCPAzureDockerKubernetesTerraformCI/CDMachine LearningLLMsRAGLLMOpsMLOpsComplianceDesign SystemsLoad BalancingHIPAAHL7/FHIR

About the role

  • Performance & Optimization - Engineer solutions for caching, batching, load balancing, and scaling LLM workloads across cloud and containerized environments.
  • About You: 5+ years of backend or full-stack software engineering experience, with 3+ years working on ML/LLM-enabled applications.

Responsibilities

  • Data & Retrieval Pipelines - Build ingestion, preprocessing, and retrieval-augmented generation (RAG) pipelines to ground LLMs in clinical and revenue-cycle data.
  • LLMOps & Observability - Design systems for model monitoring, evaluation, cost tracking, and guardrails, ensuring reliability and responsible use.
  • Security & Compliance - Implement HIPAA-ready infrastructure, data governance, and auditability for LLM-powered applications.
  • Technical Leadership - Drive end-to-end delivery of LLM backend projects, establish engineering best practices, and mentor peers in LLM system design.

Requirements

  • Familiarity with MLOps/LLMOps practices: CI/CD for models, evaluation harnesses, monitoring, and reproducibility.

Nice to have

  • Hands-on experience with RAG pipelines, vector databases, and structured-output orchestration.
  • Background in enterprise SaaS or mission-critical platforms where uptime, latency, and scale matter.
  • Knowledge of responsible AI, safety, and privacy-preserving ML techniques.
  • What's in it for you?
  • The opportunity to apply cutting-edge AI to one of the world's most important industries.
  • A leadership role with ownership over core ML/LLM systems and influence on technical direction.
  • 5+ years of backend or full-stack software engineering experience, with 3+ years working on ML/LLM-enabled applications.
  • Strong coding skills in Python (and ideally one statically typed language such as Go, Java, or TypeScript).

Skills

  • AWS/GCP/Azure, Kubernetes, Docker, Terraform, etc.
  • Cloud-native expertise: AWS/GCP/Azure, Kubernetes, Docker, Terraform, etc.

Benefits

  • SuperDial is seeking a Staff Software Engineer, Applied AI to build and scale the backend systems that power LLM applications in healthcare.
  • If you want to push LLMs beyond demos into mission-critical healthcare workflows, we'd love to hear from you.
  • Backend for LLMs - Architect and implement scalable, low-latency APIs and services that wrap, orchestrate, and optimize LLMs for healthcare use cases.
  • Cross-Functional Collaboration - Partner with product, ML engineers, and healthcare experts to translate business workflows into robust backend systems.
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