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OrumOrumSan Francisco, CA

Staff Applied AI Engineer

Lead design and production delivery of LLM-powered AI features including real-time coaching, call insights, and prospect enrichment. Requires 7+ years building and shipping ML systems with deep LLM experience.

Salary not listed
Remote7+ YOEML Engineering

About the role

What You’ll Do

  • Lead the design and delivery of AI-powered product features from idea to production
  • Build LLM-based systems for coaching insights and real-time recommendations during calls
  • Architect systems that support low latency and large-scale AI use cases
  • Define and implement AI and ML best practices across the engineering org
  • Partner with Product and Engineering to identify high-impact AI opportunities
  • Build scalable data and feature pipelines to support AI use cases
  • Establish evaluation, monitoring, and feedback loops to improve model performance
  • Mentor engineers and raise the bar on applied AI engineering practices

What You’ll Work On

  • AI-driven coaching and insights from call transcripts
  • Real-time intelligence during calls, such as next best action and signals
  • Prospect enrichment and intelligent data augmentation
  • Internal AI tools to improve engineering and product velocity

Requirements

  • 7+ years of software engineering experience with strong hands-on AI and ML experience
  • Proven track record of shipping AI and ML systems into production
  • Experience building and deploying ML pipelines for training, inference, monitoring, and continuous improvement
  • Deep experience with LLMs and modern AI tooling, including prompting, RAG, embeddings, and agents
  • Experience training and fine-tuning models for domain-specific use cases
  • Strong system design skills and ability to build scalable, reliable AI systems
  • Experience working with large-scale data systems such as pipelines, warehouses, or streaming
  • Ability to operate in ambiguity and drive technical direction independently
  • Strong product mindset focused on customer impact

Nice to Have

  • Experience with real-time or event-driven systems
  • Background in speech, NLP, or conversational AI
  • Experience building customer-facing AI products
  • Familiarity with modern data platforms such as BigQuery or ClickHouse
  • Experience building AI systems on top of scalable data platforms

Skills

LLMsMachine LearningPrompt EngineeringRAGEmbeddingsAI AgentsMl PipelinesModel Fine-TuningSystem DesignData PipelinesBigQueryClickHouseNLPReal-Time SystemsSpeech Ai

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