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Frontier Communications

AI Engineer - Go-To-Market

AI Application EngineeringUpdated on Nov 14
Full-time$120.5k - $231k /yr

About the Job

Requirements

  • A bachelor's degree or four or more years of work experience.
  • Six or more years of relevant experience, demonstrated through work and/or military experience or specialized training.
  • Strong proficiency in Python and TypeScript, with experience building web services or integrating complex APIs, especially CRM, VoIP, or sales engagement platforms.
  • A solid understanding of the large language model stack, including experience with orchestration frameworks such as LangChain/LangGraph, Strands Agents, or CrewAI.
  • Knowledge of prompt engineering, few-shot learning, and the differences between fine-tuning and retrieval-augmented generation.
  • Experience with standard software development tools such as Git and Docker, and with continuous integration and continuous delivery processes.
  • A product-oriented and revenue-focused mindset, with the ability to understand a business development representative's workflow and design AI outputs that are actionable during a live call.

Responsibilities

  • Design, deploy, and optimize generative AI solutions that reduce friction in the go-to-market engine, including agentic workflows, retrieval-augmented generation systems, and AI-native tools for sales and marketing teams.
  • Build and refine large language model-powered features and autonomous agents to enhance revenue capabilities.
  • Design and implement retrieval-augmented generation pipelines connecting proprietary data, including playbooks, product documentation, and successful call transcripts, with large language models to produce accurate, context-aware outputs.
  • Identify other go-to-market friction points and rapidly prototype AI solutions for lead enrichment, personalized outreach, and customer relationship management automation.
  • Integrate AI workflows into sales platforms such as Salesforce and Gong to support adoption by sales representatives.
  • Develop and maintain production-grade AI orchestration infrastructure, including prompt management, low-latency streaming application programming interfaces, and model evaluation frameworks.
  • Use rapid prototyping tools such as Claude Code, Codex, Lovable, and LangSmith Agent Builder to develop and deploy full-stack minimum viable products quickly.

Desired Qualifications

  • Domain expertise in go-to-market, revenue operations, or sales technology stacks such as Salesforce, HubSpot, Gong, Apollo, or Clearbit.
  • Experience building real-time audio or speech-to-text processing pipelines, such as WebRTC, Deepgram, or Whisper, for live transcription and analysis.
  • Comfort generating code with AI tools and precisely refining code, including code the candidate did not write.
  • Contributions to open-source AI projects or a portfolio of prototypes built with an AI-native toolchain.
  • Exposure to cloud-based AI services such as AWS Bedrock, Azure AI Studio, or GCP Vertex AI.
  • Experience with vector databases and semantic search concepts.
  • Experience with AI evaluation and observability tools.
  • Knowledge of agentic design patterns.

About the Company

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