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AI GTM Analyst (San Diego)

AI GTM Analyst (San Diego)

KarbonSan Diego, CA, US
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AI GTM Analyst

Karbon is the global leader in practice management software for growth-minded accounting firms. We provide an award-winning, highly collaborative cloud platform that streamlines work and communication, enabling the average accounting firm using Karbon to save 18.5 hours per week, per employee.

We have customers in 34 countries and have grown into a globally distributed team, with our people based throughout the US, Australia, New Zealand, Canada, the United Kingdom, and the Philippines. We are well-funded, ranked #1 on G2, have a fantastic team culture built on our values, are growing rapidly, and making a global impact.

We are seeking an AI and LLM-powered GTM Analyst / Lead to transform our go-to-market operations by applying advanced AI techniques to uncover and optimize the biggest revenue levers across inbound, outbound, and CSQL channels. This role prioritizes AI-driven analysis of conversion ratios, improving one key metric at a time to compound gains across the funnel. Through LLM-powered time studies and predictive modeling, this role will reveal how GTM teams allocate time, what activities drive customer health, and where AI automation can accelerate pipeline performance. This is initially a 6-month full-time position.

Key Responsibilities

1. AI-Driven Funnel Analysis & Lever Optimization (Primary Focus)

  • Use AI-powered data analysis and LLM-enhanced dashboards to identify the most impactful conversion levers across inbound, outbound, and CSQL funnels.
  • Develop and test LLM-informed hypotheses to improve one ratio at a time (e.g., lead-to-opportunity or win rates).
  • Collaborate with GTM and RevOps teams to operationalize AI-generated insights for measurable improvements.

2. LLM-Powered Time Studies (Primary Focus)

  • Deploy AI models and LLMs to analyze rep activity and time-to-serve by customer segment (e.g.,
  • Identify repetitive or low-value tasks for automation using AI agents to improve efficiency and focus on high-value activities.
  • 3. Predictive Signal Layer Creation (Secondary Focus)

  • Unify CRM, call, email, product usage, and enrichment data into an AI-driven predictive signal layer that surfaces intent, fit, and timing.
  • Train LLM-based scoring models to enhance account prioritization and sales targeting.
  • 4. Insight Automation with LLMs (Secondary Focus)

  • Use LLMs and embeddings to turn Gong calls, notes, and emails into structured AI-extracted insights.
  • Automate AI-generated summaries of objections, next-best actions, and risk signals for pipeline forecasting.
  • 5. AI-Enabled Playbooks & Dynamic Collateral (Tertiary Focus)

  • Deploy AI and LLM tools to automatically generate personalized collateral (emails, decks, and messaging) tailored to prospect profiles.
  • Implement AI-driven workflows for prospecting, reactivation, and qualification in platforms like HubSpot and Clay.
  • Qualifications

  • Hands-on experience with AI, LLMs, and vector embeddings, including tools like OpenAI API, LangChain, or similar frameworks.
  • Proven ability to design, implement, and optimize AI workflows for GTM teams, including predictive modeling and automated insights.
  • Strong understanding of data pipelines and unstructured data analysis (e.g., Gong call transcripts, email content) using LLM-based techniques.
  • Expertise in applying LLMs for summarization, insight extraction, and next-best action recommendations within GTM contexts.
  • Familiarity with AI-powered automation platforms (e.g., HubSpot AI, Clay, or custom GPT-based agents).
  • Deep knowledge of GTM tech stacks (e.g., Salesforce, Gong, HubSpot, Outreach) and experience leveraging AI integrations to extract maximum value from these tools.
  • Solid grounding in GTM funnel metrics and the ability to apply AI analytics to improve conversion ratios sequentially.
  • Proficiency in SQL or Python for data manipulation and AI model integration is a plus.
  • Why Work at Karbon

  • Gain global experience across the USA, Australia, New Zealand, UK, Canada and the Philippines
  • Excellent benefits package including :
  • Paid Flexible Time Off with an encouraged 3 weeks use per year
  • Company paid medical for you and eligible spouse / partner and dependents
  • Company paid dental and vision and eligible spouse / partner and dependents
  • Fully company funded short and long term disability
  • Fully company paid life insurance
  • 401(k) with company matching
  • Flexible Spending Account
  • Up to 8 weeks paid parental leave
  • Work-from-home stipend
  • Work with (and learn from) an experienced, high-performing team
  • A collaborative, team-oriented culture that embraces diversity, invests in development and provides consistent feedback
  • Be part of a fast-growing company that firmly believes in promoting high performers from within
  • The estimated base salary range for this role is :

    $100,000 - $130,000 USD

    Karbon embraces diversity and inclusion, aligning with our values as a business. Research has shown that women and underrepresented groups are less likely to apply to jobs unless they meet every single criteria. If you've made it this far in the job description but your past experience doesn't perfectly align, we do encourage you to still apply. You could still be the right person for the role!

    We recruit and reward people based on capability and performance. We don't discriminate based on race, gender, sexual orientation, gender identity or expression, lifestyle, age, educational background, national origin, religion, physical or cognitive ability, and other diversity dimensions that may hinder inclusion in the organization.

    Generally, if you are a good person, we want to talk to you.

    If there are any adjustments or accommodations that we can make to assist you during the recruitment process, and your journey at Karbon, contact us at people.support@karbonhq.com for a confidential discussion.

    At this time, we request that agency referrals are not submitted for this position. We appreciate your understanding and encourage direct applications from interested candidates. Thank you!

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